mercredi 24 juillet 2013

Magic Quadrant for Data Integration Tools

A lire sur:

17 July 2013 ID:G00248961
Analyst(s): Eric Thoo, Ted Friedman, Mark A. Beyer


Opportunities in the data integration tool market favor breadth of functionality in a well-integrated product set. Offerings that are flexible with regard to time to value, broad applicability, cost over value and data management synergy harness market momentum to capitalize on demand trends.

Market Definition/Description

The data integration tool market comprises vendors that offer software products to enable the construction and implementation of data access and data delivery infrastructure for a variety of data integration scenarios, including:
  • Data acquisition for business intelligence (BI), analytics and data warehousing: Extracting data from operational systems, transforming and merging that data, and delivering it to integrated data structures for analytics purposes. BI and data warehousing remain mainstays of the demand for data integration tools. The variety of data and context for analytics is expanding as emergent repositories, such as Hadoop distributions for supporting big data, in-memory database management systems (DBMSs), and logical data warehouse architectures, increasingly become parts of the information infrastructure.
  • Consolidation and delivery of master data in support of master data management (MDM): Enabling the consolidation and rationalization of the data representing critical business entities, such as customers, products and employees. MDM may or may not be subject-based, and data integration tools can be used to build the data consolidation and synchronization processes that are key to success.
  • Data migrations/conversions: Although traditionally addressed most often via the custom coding of conversion programs, data integration tools are increasingly addressing the data movement and transformation challenges inherent in the replacement of legacy applications and consolidation efforts during mergers and acquisitions.
  • Synchronization of data between operational applications: In a similar concept to each of the previous scenarios, data integration tools provide the ability to ensure database-level consistency across applications, both on an internal and an interenterprise basis (for example, involving data structures for software as a service [SaaS] applications or cloud-resident data sources), and in a bidirectional or unidirectional manner.
  • Interenterprise data sharing: Organizations are increasingly required to provide data to, and receive data from, external trading partners (customers, suppliers, business partners and others). Data integration tools are relevant in addressing these challenges, which often consist of the same types of data access, transformation and movement components found in other common use cases.
  • Delivery of data services in a service-oriented architecture (SOA) context: An architectural technique, rather than a use of data integration itself, data services represent an emerging trend for the role and implementation of data integration capabilities within SOAs. Data integration tools will increasingly enable the delivery of many types of data services.
Gartner has defined multiple classes of functional capability that vendors of data integration tools provide to deliver optimal value to organizations in support of a full range of data integration scenarios:
  • Connectivity/adapter capabilities (data source and target support): The ability to interact with a range of different types of data structure, including:
    • Relational databases
    • Legacy and nonrelational databases
    • Various file formats
    • XML
    • Packaged applications, such as CRM and supply chain management
    • SaaS and cloud-based applications and sources
    • Industry-standard message formats, such as electronic data interchange (EDI), Swift and Health Level Seven International (HL7)
    • Externalized parallel distributed processing (such as Hadoop Distributed File System [HDFS] and other NoSQL-type repositories)
    • Message queues, including those provided by application integration middleware products and standards-based products (such as Java Message Service [JMS])
    • Data types of a less structured nature, such as social media, email, websites, office productivity tools and content repositories
    • Emergent sources, such as data on in-memory DBMSs, mobile platforms and spatial applications
  • Data integration tools must support different modes of interaction with this range of data structure types, including:
    • Bulk acquisition and delivery
    • Granular trickle-feed acquisition and delivery
    • Changed data capture (CDC) — the ability to identify and extract modified data
    • Event-based acquisition (time-based or data-value-based)
  • Data delivery capabilities: The ability to provide data to consuming applications, processes and databases in a variety of modes, including:
    • Physical bulk data movement between data repositories
    • Federated views formulated in memory
    • Message-oriented movement via encapsulation
    • Replication of data between homogeneous or heterogeneous DBMSs and schemas
  • In addition, support for the delivery of data across the range of latency requirements is important, including:
    • Scheduled batch delivery
    • Streaming/near-real-time delivery
    • Event-driven delivery of data based on identification of a relevant event
  • Data transformation capabilities: Built-in capabilities for achieving data transformation operations of varying complexity, including:
    • Basic transformations, such as data type conversions, string manipulations and simple calculations
    • Intermediate-complexity transformations, such as lookup and replace operations, aggregations, summarizations, deterministic matching, and the management of slowly changing dimensions
    • Complex transformations, such as sophisticated parsing operations on free-form text and rich media
  • In addition, the tools must provide facilities for developing custom transformations and extending packaged transformations.
  • Metadata and data modeling capabilities: As the increasingly important heart of data integration capabilities, metadata management and data modeling requirements include:
    • Automated discovery and acquisition of metadata from data sources, applications and other tools
    • Discerning relationship between data models and business process models
    • Data model creation and maintenance
    • Physical to logical model mapping and rationalization
    • Defining model-to-model relationships via graphical attribute-level mapping
    • Lineage and impact analysis reporting, via graphical and tabular format
    • An open metadata repository, with the ability to share metadata bidirectionally with other tools
    • Automated synchronization of metadata across multiple instances of the tools
    • Ability to extend the metadata repository with customer-defined metadata attributes and relationships
    • Documentation of project/program delivery definitions and design principles in support of requirements definition activities
    • Business analyst/end-user interface to view and work with metadata
  • Design and development environment capabilities: Facilities for enabling the specification and construction of data integration processes, including:
    • Graphical representation of repository objects, data models and data flows
    • Workflow management for the development process, addressing requirements such as approvals and promotions
    • Granular, role-based and developer-based security
    • Team-based development capabilities, such as version control and collaboration
    • Functionality to support reuse across developers and projects, and to facilitate the identification of redundancies
    • Support for testing and debugging
  • Data governance support capabilities (via interoperation with data quality, profiling and mining capabilities): Mechanisms to work with related capabilities to help the understanding and assurance of data quality over time, including interoperability with:
    • Data profiling tools
    • Data mining tools
    • Data quality tools
  • Deployment options and runtime platform capabilities: Breadth of support for the hardware and operating systems on which data integration processes may be deployed, and the choices of delivery model; specifically:
    • Mainframe environments, such as IBM z/OS and z/Linux
    • Midrange environments, such as IBM System i (formerly AS/400) or HP Tandem
    • Unix-based environments
    • Windows environments
    • Linux environments
    • Traditional on-premises (at the customer site) installation and deployment of software
    • Cloud deployment support as a multitenant implementation but requires organizations deploy software in cloud infrastructure
    • Platform as a service (provided and consumed as a cloud service where clients don't need to deploy software in cloud infrastructure)
    • In-memory infrastructure
    • Server virtualization (support for shared, virtualized implementations)
    • Parallel distributed processing (such as Hadoop and MapReduce)
  • Operations and administration capabilities: Facilities for enabling adequate ongoing support, management, monitoring and control of the data integration processes implemented via the tools, such as:
    • Error handling functionality, both predefined and customizable
    • Monitoring and control of runtime processes, both via functionality in the tools and interoperability with other IT operations technologies
    • Collection of runtime statistics to determine use and efficiency, as well as an application-style interface for visualization and evaluation
    • Security controls, for both data in flight and administrator processes
    • A runtime architecture that ensures performance and scalability
  • Architecture and integration capabilities: The degree of commonality, consistency and interoperability between the various components of the data integration toolset, including:
    • A minimal number of products (ideally one) supporting all data delivery modes
    • Common metadata (a single repository) and/or the ability to share metadata across all components and data delivery modes
    • A common design environment to support all data delivery modes
    • The ability to switch seamlessly and transparently between delivery modes (bulk/batch vs. granular real-time vs. federation) with minimal rework
    • Interoperability with other integration tools and applications, via certified interfaces and robust APIs
    • Efficient support for all data delivery modes, regardless of runtime architecture type (centralized server engine versus distributed runtime)
  • Service enablement capabilities: As acceptance of data service concepts continues to grow, data integration tools must exhibit service-oriented characteristics and provide support for SOA deployments, such as:
    • The ability to deploy all aspects of runtime functionality as data services
    • Management of publication and testing of data services
    • Interaction with service repositories and registries
    • Service enablement of development and administration environments, so that external tools and applications can dynamically modify and control the runtime behavior of the tools

Magic Quadrant

Figure 1. Magic Quadrant for Data Integration Tools
Figure 1.Magic Quadrant for Data Integration Tools
Source: Gartner (July 2013)

Vendor Strengths and Cautions

Actian-Pervasive Software

Located in Redwood City, California, Actian acquired Pervasive Software in April 2013 and offers the following data integration products: Data Integrator, DataCloud and DataRush. The vendor's customer base for this product set is estimated at more than 6,000 companies.
  • Long pedigree of targeted offerings: Actian-Pervasive has been an active participant in the data integration tool market for a long time, beginning in 1982. By staying focused on targeted aspects of the overall data integration market, Actian-Pervasive offers real-time messaging-style solutions and bulk/batch-oriented data delivery. Customers like the diverse connectivity for data sources and targets, and the support for industry-standard message formats. Additionally, the DataRush technology continuously scores data for existing analysis as it moves through a data service bus in enabling rapid assignment of each new data point to analytic outcomes.
  • Growing resources: Actian's acquisition of Pervasive provides significantly larger financial resource potential for further enhancement of Data Integrator. Additionally, the capabilities in Actian's global reach are significantly greater than Pervasive. At the same time, Actian has begun expanding its EMEA presence to further enhance its larger corporate global reach.
  • Easily embedded and complementary solutions: Actian-Pervasive has been able to develop some meaningful, patented technology that generally enhances a position to embed its data integration solutions within other technology solutions. Customers report the two most significant strengths are the small footprint and the wide array of connectors/adapters that result in a wide array of solution-oriented benefits. One benefit directly attributable to connectivity and footprint is the ease with which Data Integrator is embedded in other solutions, in the offerings of independent software vendors (ISVs) and for modernizing on-premises legacy implementations. A second benefit is cited by customers in leveraging the product's ability to address performance requirements for high data throughput.
  • Continuing with management continuity: The acquisition makes sense for Actian, which also recently acquired ParAccel. In combination with its Action Apps strategy (embedded analytics reflecting data changes), the Pervasive acquisition and the long-standing Pervasive business model for embedding its offerings make sense for Actian. Pervasive's acquisition was unwelcome in the beginning, although there were initial indications that Pervasive staff were pleased with the access to broader and deeper resources, and public announcements were used to expose the effort to put pressure on the Board and Officers of Pervasive. Importantly, key personnel have been retained up to this point, but Actian must be persistent and consistent in retaining valuable talent while carefully addressing redundant positions. Redundant positions do not equal redundant people.
  • Upgrade and deployment experiences: Customers readily point out that there are issues in migrating between versions. Specifically, customers call out that the repositories are not entirely compatible and that new features are not always market-ready (for example, bugs and issues were reported regarding iHub in version 9 and iHub being replaced with new functionality in version 10; other customers reported an almost pendulum effect of a stabilizing release followed by a next release that removed functionality). Actian-Pervasive indicates that the upgrade to version 10 was significant, which explains upgrade difficulties cited in customer experiences when requiring assistance. Many respondents also reported that the interface is aging (even version 10), and is sometimes lacking functionality and does not support the development of cross-platform deployments very well.
  • Uneven documentation, uneven learning curve: Many customers report issues with documentation and a lack of communication and coordination for upgrade support and bug fixes. Customer reviews are largely lacking in comments about professional services quality, with only minor comments that they need to improve. Considering the learning curve and documentation in combination, customers report that developers do not find online help or built-in help very useful, and this forces developers to determine their own best practices, which further extends the learning curve for the tools. A small number of customers hope the new user community will provide a better resource in this area.


Located in Chicago, Adeptia offers the Adeptia Enterprise Business Integration Management (EBIM) Suite. The vendor's data integration tool customer base is estimated at more than 380 companies.
  • Coverage of core capabilities: Adeptia supports the core requirements in the breadth of connectivity and adapters, bulk/batch data delivery, and granular data capture and propagation. Reference customers identify the strength of its ease of use, and the tool's ability to support business personnel's participation in building and maintaining integration processes suited to their specific needs as key points of value.
  • Integrated product offering: Adeptia provides its range of data integration functions in a single tool suite, which reduces the complexity for buyers and streamlines the process for supporting integration activities and processes, such as data mapping, flow design and shared data definitions across use cases.
  • Spans both data integration and application integration: Through a multidisciplinary tool platform, Adeptia's EBIM Suite provides a single environment for data integration capability together with the platform's enterprise service bus and business process management functions. This aligns well with demand trends for supporting data integration activities so that competency teams can seamlessly implement multiple integration infrastructures in a synergistic way.
  • Recognition and capabilities beyond extraction, transformation and loading (ETL) for data integration: Adeptia is deployed with a strong bias toward process-oriented bulk/batch and transactional data movements, and more market experience is needed with other methods of data integration styles for data delivery. Increasing requirements such as data replication and synchronization put Adeptia at a competitive disadvantage relative to providers that have a reputation for addressing a broader range of data integration styles. Adeptia is evaluating a partnership to provide data replication and synchronization capabilities.
  • Degree of metadata support: Customer references indicate gaps in various aspects of Adeptia's metadata management and modeling. Documentation for field definitions is used as basic references, although implementations increasingly require comprehensive support of metadata discovery, lineage and dependency reporting, which is of growing importance when integrating a large volume and diversity of datasets.
  • Customer support and service experience: While Adeptia's references reflect satisfaction regarding the perception and price points of the tool, concerns are cited on the quality of support. Areas of challenges reported include support for issue resolution, product upgrade, initial installation and setup, and technical help documentation. These are common issues for vendors, which evolve as growing businesses but are simultaneously challenged to keep up with customer demand.

Composite Software

Located in San Mateo, California, Composite Software offers the following data integration products: Composite Data Virtualization Platform (which consists of Composite Information Server, Composite Discovery and adapters to access data sources), Composite Active Cluster and Composite Discovery. The vendor's customer base for this product set is estimated at more than 200 companies. At this writing, Cisco has made an offer to acquire Composite Software, which has accepted the offer, but the acquisition is underway and not yet completed.
  • Solid coverage of core capability: Aligned to the rising interest, acceptance and importance of federation or virtualization to the overall data integration market, Composite Software brings just over 10 years of research and development and licensed customer experience to bear on the federation/virtualization aspects of the data integration market. While many early federation tools struggled and were acquired or went out of business, Composite Software followed a deliberate and highly targeted approach to the market by first identifying specific niche fulfillment areas and then developing features and functionality to address specific performance issues unique to federation, compared with other types of data integration. For example, the use of multitiered caching to enhance both the design and performance of the federation processing was focused specifically on the best approach to optimize when to refresh data from sources (all data has differing refresh rates and thus cache layers do not need to be universally updated at the same time).
  • Track record and partner channels: Due to the vendor's longer successful track record in federation capabilities, it has developed an efficient partnering network, which includes implementers and other data integration software vendors. HP, Hortonworks, IBM, Infosys, MicroStrategy and Tibco Software are among Composite Software's active vendor partners, and include the range of joint marketing to embedded solutions for federation or semantic data access support. The vendor also has partnerships with Progress Software for Progress Corticon in its business rule management solution and with BMC for a similar solution that provides federation or virtual data access to support heterogeneous data access without requiring point-to-point physical data transformation.
  • Connectivity support and links to related capabilities: Composite Information Server supports connectivity to relational databases, prerelational legacy data types, flat files, XML, packaged application prebuilt access and HDFS. In addition, templates/prebuilds for EDI, HL7, SWIFT and various XML dialects are available to accelerate connectivity to these source types. The vendor has partially addressed the frequent challenge to federation technology — output for point-to-point physical transformation — in two ways. Information Server can output staging files from its various caching tiers, which can then be used for loading a database (either with further transformation or simply using bulk loaders from the DBMS). In addition, Information Server, in its partnership with IBM, can write directly to the Netezza database (using its cache structure as a database design).
  • Breadth of functionality: As Composite Software's data integration focus is predominantly on virtual federation of data and limited bulk/batch data delivery support, organizations seeking providers with a breadth of data integration styles find the product set to be of narrow positioning relative to competitors in this market. Composite Software is reported as "somewhat heavy" in its design and deployment of virtual data views. The lack of development workflow management in the tool and missing data quality prebuilds require that developers be self-managed and aware of issues that emerge when source data is accessed directly, as well as the types of collisions that occur and the rationalizations necessary to remedy such situations. Developers should be accomplished data architects or system analysts who understand the flow of data.
  • Availability of skill and deployment experience: The vendor's implementation experience base among its customers is small. As a result, there is a lack of adequately skilled implementers in the market, and a resultant low volume of commonly understood practices and fixes for implementation issues. This causes further difficulty as customers report that documentation (including in-system, context-based documentation) is weak. In the area of support services, Cisco has a long history of recognition for quality support from independent ratings systems; however, it is unclear if this will translate to the data management and integration market as the acquisition moves forward.
  • Customer experience: Customer support is uneven, with some customers reporting satisfactory support while others cite frustration with account and monitoring hygiene concerns. For example, case logs of issues, hot fixes in place, which adapters are in use, etc., result in wasted time during support contacts. Composite Software recently established a customer tracking database for issues and issue resolution, but this is a newly deployed support system. Additionally, system metadata can persist for long periods of time in the operations logs, but the vendor has not developed any guidelines from its customer base for best practices in this area, making it sometimes difficult to track issue resolution if the data is not retained. Overall, however, Composite Software's customers rate the vendor at almost the average scoring for customer experience, which means these items appear to be symptoms of a small company becoming larger, and it is only a question of Composite responding with improvements to its support organization as the customer base grows larger and the use cases become more diverse. Customers also report that there is some inconsistency between versions, with previous functionality sometimes limited in subsequent releases (such as reduced Web services support).


Located in Armonk, New York, IBM offers the following data integration products: IBM InfoSphere Information Server Enterprise Edition (including InfoSphere Information Server for Data Integration, InfoSphere Information Server for Data Quality and InfoSphere Business Information Exchange), InfoSphere DataStage, InfoSphere Federation Server, InfoSphere Data Replication and WebSphere Cast Iron Cloud Integration. The vendor's customer base for this product set is estimated at approximately 9,600 companies.
  • Breadth of functionality: IBM provides an extensive range of data integration functionality, including bulk-batch data movement (ETL), CDC and propagation, data replication, and data federation/virtualization. IBM continues to demonstrate a strong vision in the market for extensive data integration capabilities comprising products sold both independently and in various InfoSphere Information Server bundles. Reference customers routinely cite as key strengths (and their reasons for selecting IBM) the sheer breadth of functionality of the vendor's product set across the range of data integration styles, the degree of integration between the components of the portfolio via common metadata and the scalability they can achieve in the face of high-volume requirements.
  • Installed base and diversity of usage: IBM's tools are often deployed as an enterprisewide standard, and many customers have significant numbers (10+) of developers using them. The scope and scale of the implementations is often large. This is reflective of and contributes to the large and growing pool of skills available to the market. While the customer base shows very heavy usage in BI/analytics and data warehouse scenarios, reference customers also show diversity across a range of application types (including MDM, data migration and operational application integration). During 2012, IBM was able to achieve solid growth of its data integration tool business, reflecting strong execution.
  • Alignment with information infrastructure and enterprise information management (EIM) trends: With the growing activity toward modernization of information infrastructure in support of EIM goals, IBM's capabilities are well-aligned with the intent of buyers. Customers view the broad and deep metadata management functionality as critical to the early stages and ongoing value in their EIM programs, and believe this enables them to derive greater value from IBM's data integration tools. Version 9.1 of Information Server introduced deeper support for Hadoop and the new InfoSphere Data Click functionality aimed at enabling power users to perform self-service data preparation for analytics purposes. The 2013 product road map focuses on more technical enhancements related to deeper Hadoop and cloud support, as well as expanded ongoing performance enhancements and integration with other InfoSphere offerings, such as information life cycle management.
  • Usability challenges: While reference customer feedback shows notable improvement in satisfaction with overall customer experience relative to prior years, customers continue to cite complexity, primarily in initial deployment and migrations/upgrades between versions, as challenging. They want IBM to continue to simplify the tools, increase consistency of user interface and management capabilities across the product set, and ease the process of application of fixpacks. Broadly available skills in the market help address some of these challenges, but IBM must continue to improve here.
  • Cost model: While customers recognize a reasonable connection between IBM's data integration tool pricing and anticipated value, reference customers and many prospective customers indicate that prices can be prohibitive, and their perception is of a high total cost of ownership (TCO) and sometimes a sense that IBM is proposing solutions with extraneous functionality (particularly when the customer's needs may be modest in scope and complexity). When prospects eliminate IBM from competitive evaluations and choose in favor of other vendors, this is by far the most common reason. IBM's packaging options, including Enterprise and Workgroup editions and data warehousing offerings, are aimed at mitigating these concerns by providing commonly used bundles of components for functionality required in a specific use case, and entry-level prices suitable for smaller customers and implementations.
  • Balance of emphasis across product set: While the IBM set of offerings in this market is extensive, the vendor's priorities appear to be heavily oriented toward physical data flow and predominantly focused on Information Server for Data Integration (InfoSphere DataStage) for bulk/batch workloads. With the growing interest in logical data warehouse architectures and the virtualized provisioning of data, the limited emphasis on InfoSphere Federation Server (both in the product road map and as a significant part of the portfolio in IBM's sales and marketing execution) represents a gap relative to market demand.


Located in Redwood City, California, Informatica offers the following data integration products: Informatica Platform (including these components: PowerCenter, PowerExchange, Data Services, Data Replication, Ultra Messaging, B2B Data Exchange and Cloud Data Integration). The vendor's customer base for this product set is estimated at more than 5,000 companies.
  • Range of functionality across data integration styles: Informatica provides support for all key data integration styles, including bulk-batch ETL, real-time and granular data flow via CDC/propagation and replication, data federation/virtualization, and messaging. This range of functionality aligns well with evolving demands in the data integration tool market. Informatica continues to develop points of linkage and integration between and across these data integration styles, enabling customers to leverage them in a synergistic manner. Recent reference customer interactions reflect deployment of an increasing number of these capabilities and in complex scenarios. These Informatica deployments tended to involve a broader range of data source types, a greater diversity of use cases and a wider footprint in the enterprise (63.6% of customers in the sample indicated their deployments involved six or more business functions) than most of its competition. In addition, customers indicate a positive perception about Informatica's vision and direction in the market.
  • Market presence and proven capabilities: Informatica appears more frequently than any other vendor on the shortlist of organizations performing competitive evaluations in this market. The Informatica customer base reflects a diverse set of use cases and a good number of large deployments in which the vendor is the enterprisewide standard for data integration tooling. Reference customers cite the core functionality of the platform (primarily the range of connectivity, transformation capabilities, scalability and developer productivity), as well as the great availability of skills, resources and know-how about the vendor's products, as key strengths and reasons for their ongoing use of the technology. The addition of the PowerCenter Express offerings, aimed at limited-scale requirements and budget-constrained organizations, should enable Informatica to expand this presence into newer segments of the market.
  • Deployment modes and platform support: At the core of Informatica's platform capabilities and product strategy is the ability to design mapping and transformations centrally and deploy for execution on many platforms in a seamless manner. Through the architecture Informatica calls a "virtual data machine" (marketed by the vendor as Vibe), customers can design mappings and transformations which can then be deployed on runtime platforms of many types (including emerging big data technologies such as Hadoop) to achieve distributed data integration processes. Regardless of runtime platform, these processes are based on the same Informatica skills, development approaches and management/administrative capabilities the customers already have in place. The same concept applies to cloud-based and hybrid (on-premises and cloud combinations) deployments. This aligns well with the concept of common (platform-independent) data integration capabilities required for modern information infrastructures.
  • Customer experience as vendor size and product breadth grows: Customers appreciate the breadth of capabilities that Informatica has amassed and the vendor's expanding vision for information infrastructure, but they also note some challenges that these advancements bring. Recent reference customer interactions indicate a desire for less complex version upgrades and an overall shorter learning curve. Related to these points, reference customer deployments indicated an increase in average time to value relative to prior years. Informatica customers routinely address complex scenarios, which may contribute to this feedback. However, as it continues to grow its product set and expand its functionality, the vendor must stay focused on retaining a positive product deployment and management experience for its customers.
  • Pricing: Informatica's price points and pricing model remain challenges, with many reference customers in a recent sample and other Informatica customers overall noting them as among the most significant issues they find in working with the vendor. This includes both the initial cost of purchasing Informatica's products and the perceived high cost of add-on options, which some customers cite as an inhibitor for them in adding further functionality. The recent announcement of PowerCenter Express offerings is a significant move by the vendor to address these issues. However, for larger enterprises and existing customers, pricing will remain a challenge.
  • Consistency in sales and marketing execution: Informatica stumbled in 2012 (as evidenced by below-market-average growth, as well as a decline in software license revenue on a quarterly, year-over-year comparison basis from 2Q12 through 1Q13). Gartner believes this was the result of sales execution issues (particularly in Europe) and a marketing and sales focus toward emerging use cases (for example, big data and cloud), which did not optimally align with the primary interests of the mainstream of the market. In addition, feedback from Informatica customers indicates a less stable and consistent sales experience relative to prior years. The vendor is rebalancing its messaging in 2013, and has made some sales leadership changes. The 1Q13 results moved in a positive direction, and customers and prospects should review Informatica's latest quarterly results to determine if these changes have contributed to an ongoing trend of improvements.

Information Builders

Located in New York, Information Builders offers the following data integration products: iWay Service Manager, iWay DataMigrator, iWay DataMigrator CDC and iWay Universal Adapter Suite. The vendor's customer base for this product set is estimated at approximately 650 companies.
  • Range of product functionality: Information Builders offers capabilities in all major data integration styles, including physical bulk-batch and real-time granular data movement and delivery (via its DataMigrator ETL tool), message-oriented integration and data federation (supported by the Service Manager product), and an extensive array of adapters for connectivity across all common platforms, applications and data sources. This breadth enables the vendor to support a broad range of use cases and implementations. This is evidenced by data from recent reference customer interactions, which shows that Information Builders' users are supporting a much more diverse and balanced set of use cases than most of its competitors, as well as by customer feedback citing the degree of integration and performance/scalability of the various products as key strengths.
  • Alignment with key information infrastructure trends: The breadth of the product portfolio and Information Builders' experience in deployments of various styles aligns it well with contemporary trends beyond this specific market. The vendor's strength in SOA and application integration positions it well as those technology types and disciplines continue to converge with the data integration space. The addition of data quality and MDM tooling to the portfolio also enables Information Builders to increasingly position itself as critical to the modern information infrastructure, where governance of data grows equally important to integration.
  • BI and analytics platform market presence and customer relations: Information Builders' long presence and strong brand in the BI and analytics platform market are great strengths in enabling it to engage both existing customers and prospects. A substantial number of the vendor's customers indicate their selection of the vendor's data integration tools was strongly influenced by the fact that they already used other Information Builders products (most often WebFOCUS). The vendor can continue to use this pull-through sales traction to further improve its execution. Regardless of the range of product usage, reference customers often indicate a close and positive working relationship with the vendor and good perceptions of product cost relative to value.
  • Product experience and documentation: While reference customers view the range of functionality and power of Information Builders' products as a strength, many cite product complexity, a longer learning curve and insufficient documentation as areas in which the vendor could improve. In addition, customers also occasionally cite challenges with upgrades to new major releases of the product set, specifically indicating that new versions have been known to remove fixes applied to previous versions, thereby reintroducing bugs. These issues speak to a continued need for Information Builders to reduce product complexity, improve training resources, and increase the focus on quality assurance and release management. The vendor states that the iWay 7 release is expected to simplify complexity and ease version upgrade issues moving forward.
  • Mind share in data integration tool market: While the Information Builders brand is strong in BI and analytics, the vendor often struggles to gain mind share as an integration generalist. The vendor appears with low frequency in competitive evaluations, and its data integration tools often seem to take a lower priority in the messaging and positioning of the vendor. This is also reflected in the vendor's installed base, where customers often deploy its data integration tools in support of individual projects, rather than as a broadly used enterprise standard.
  • Marketing execution and focus: With the current focus of the vendor on growing the data quality and MDM components of its Information Asset Management Platform offering (the new name the vendor has given to the collection of its integration products, alongside its former EIM Suite offerings for data quality and MDM), the vendor must continue to emphasize heavily how the data integration tooling is critical to enabling infrastructure for any and all information-related initiatives. This is the mindset customers have when approaching this market, and Information Builders must, therefore, also focus its sales and marketing activities to capture data integration opportunities in their own right.


Located in Redmond, Washington, Microsoft offers the following data integration products: SQL Server Integration Services (SSIS; offered via its SQL Server DBMS license) and BizTalk Server. The vendor's customer base for this product set is estimated at more than 13,000 companies.
  • Aligned support of data and process-oriented integration: Offering access to almost any commercially available relational database source and target as well as supporting ODBC, OLE DB and text file access, SSIS is most often used to put data into SQL Server, but can also target these other platforms or environments. Along with BizTalk Server, SSIS integrate data from business workflows in ERP and other enterprise applications. When used together with SQL Server StreamInsight, SSIS can read complex events and streaming data for use in data integration processes. Data quality operations can be embedded in SSIS-driven data integration processes by using Data Quality Services (DQS) in SQL Server 2012.
  • Familiar interfaces enable productivity and time to value: When cost is combined with ease of use (consistently cited by users for four years), it makes it very difficult to choose another tool once Microsoft SQL Server is already deployed in related use cases, such as data marts, data warehouses, operational data stores and even application integration services (when combined with BizTalk Server). In enabling faster time to value using familiar interfaces, Microsoft aims to enhance the ability of users to perform data mashups using Excel interfaces in support of user-driven data integration activities, which takes advantage of the underlying capability of SSIS to access various data sources.
  • Implementations reinforce low price: As in years past, Microsoft products are among the most familiar to implementers when considering interfaces, development tools and functionality. The low-cost footprint continues to be attractive (it is among the very lowest of commercially available data integration tools). Included with the SQL Server DBMS license and as a solid contender in the data integration tool market, SSIS presents a de facto choice, unless consciously eliminated from data integration solutions in organizations already using SQL Server. The net result is that Microsoft offers a different software model than most enterprise-class competitors, one that focuses on TCO and ease of use to a much greater extent than their competitors.
  • Market penetration in enterprise-scale adoptions: Implementations reflect increasing departmental-level deployments that orientate toward less-sophisticated usage. SQL Server SSIS is an embedded functionality in SQL Server, and any Microsoft SQL Server customer can utilize SSIS (and many do). Most customers indicate that SSIS begin as a departmental or project-based approach. As the product use becomes more pervasive, these customers are then confronted with trying to standardize their practices among competing approaches. This forms a barrier to enterprise adoption, and organizations choosing to use SSIS as an enterprise tool should move away from the usual model of letting Microsoft users deliver unarchitected solutions in the beginning and instead create standards for deployment very early.
  • Fragmentation of advanced skill base: Organizations that purchase SQL Server solely to use SSIS will likely need to utilize professional implementers to help build enterprise-scale solutions. In part, this is to answer the enterprise-scaling issue already discussed. But, more importantly, with a wide availability of highly varied implementation skills in the market, it is difficult to identify Microsoft best practitioners. Organizations should be aware of the various levels of Microsoft Professional Certifications and match them with their specific project and enterprise architecture demands.
  • Integration and deployment have some challenges: Reference customers report overall satisfaction with the tools; however, there are specific issues with integrating SSIS with wider data-management-related technologies and some connectivity issues with more traditional sources (challenges are cited for AS/400, z/OS and VMS environments). Customers reported a lack of metadata support as a weakness that affects metadata discovery, lineage and dependency reporting capabilities. References also expressed that guidelines and approaches for integrating SSIS with SOA services are difficult to find, much less follow (noting orchestration and job flow issues).


Located in Redwood Shores, California, Oracle offers the following data integration products: Oracle Data Integrator (ODI), Oracle Data Service Integrator, Oracle GoldenGate and Oracle Warehouse Builder (OWB). The vendor's customer base for this product set is estimated at approximately 3,800 companies.
  • Comprehensive functionality and alignment of offerings: Oracle's unified product development approach for data integration tooling as part of the Oracle Information Management Strategy offers breadth and depth of functionality and aligns to its broader portfolio of data management offerings. ODI provides capabilities for bulk/batch data movement, and Oracle GoldenGate centers on CDC and real-time data delivery. Oracle Data Service Integrator provides data federation/virtualization capabilities. These primary data integration products, along with the message-oriented functionality of Oracle WebLogic Suite, enable the vendor to support each of the major data delivery styles in this market.
  • Diversity of usage scenarios: ODI and Oracle GoldenGate continue to grow in adoption. References using ODI like its ease of use and standardization support of reusable artifacts to improve developers' productivity, aided by knowledge modules and model-driven management of extensible data flows and mapping. These customers also exhibit a mix of use cases and project types, with the vast majority using the tools in support of BI, operational data consistency and data migration. Oracle GoldenGate continues to be cited for its strength in enabling mission-critical data replication and synchronization in heterogeneous data and application environments. Aligning to demand, the 12c release of Oracle's product portfolio sets out to enhance product integration between ODI and Oracle GoldenGate's offerings, optimization of replication workload through in-memory management, and integrated usage of data integration tooling with data quality and MDM capabilities.
  • Wide leverage of application- and data-oriented customer bases: Recognition of Oracle as a comprehensive provider for potential data integration and other data management functionality requirements, such as data quality tools and MDM solutions, is cited as a key point of value for selecting the vendor's tools in this market. Oracle's ability to offer data integration tools in conjunction with broad application- and data-oriented solutions continues to create opportunities for adoption. Oracle leverages its market penetration, global presence and proven viability by cross-selling to its very large application, BI/analytics, DBMS and database appliance customer bases.
  • Product migration support: The increasing adoption of ODI as a replacement for OWB, due to OWB's end of life, is raising demand in enterprises for an easier migration path, and the difficulties of tool migration are cited as a significant challenge. In supporting existing usage and a phased migration path, runtime execution of OWB processes through the ODI console is anticipated in the upcoming release of ODI, while Oracle plans to make available a migration toolkit for supporting the migration of OWB artifacts to ODI.
  • Interoperability across products: Customers cited desires for greater metadata management support and simpler ways to achieve interoperability across Oracle's product set, in order to facilitate seamless use of multiple products to achieve a range of data integration functionality. Oracle's road map for increasing interchange capabilities that link data federation/virtualization tooling more closely to the rest of the product set represents an ongoing focus on tightening product interoperability. With the growing interest in virtualized provisioning of data (such as logical data warehouse architectures), requirements to seamlessly operate bulk/batch-style data movements with virtual federation approaches will require increased emphasis, although usage of Oracle's data federation/virtualization offering remains small relative to major competitors in this market.
  • Skills requirements and cost of ownership: A desire for better availability of skilled resources is cited as a challenge, to help address implementations, both in initial setup (particularly for complex projects) and in version upgrades and technical integration with other software in Oracle's product portfolio. Satisfaction with Oracle's pricing method and perception of value relative to cost are reported as relatively low, compared with most of its competitors. Concerns with increased efforts to interoperate multiple products generate perceptions of escalating implementation costs in achieving various required functionality.


Located in Walldorf, Germany, SAP offers the following data integration products: SAP Data Integrator, SAP Data Services, SAP NetWeaver Process Orchestration, SAP Sybase Replication Server and SAP Hana Cloud Integration for Data Services. The vendor's customer base for this product set is estimated at more than 11,000 companies.
  • Breadth of functionality: The breadth of functionality available across SAP's portfolio addresses a wide range of data delivery styles, and positions data integration tooling in synergy with SAP's data quality and MDM offering, which aligns well with demands. The breadth of data integration functionality spans bulk-batch ETL, data federation, message-oriented data delivery and CDC/replication. The combination of these capabilities allows the vendor to attract customers seeking support for a variety of data integration patterns and use cases. The majority of deployments center around the SAP Data Services product for strong bulk-batch data delivery. The 4.2 release of SAP Data Services aims to tighten integration between bulk data delivery functionality and the replication and synchronization offering of SAP Sybase Replication Server, and enhances interoperability between data integration tooling and SAP Hana for supporting big data initiatives.
  • Alignment with information infrastructure and governance trends: SAP's approach, based on a single runtime platform in SAP Data Services that tightly integrates data quality and text data processing capabilities along with data integration functionality, is described by customers as increasingly relevant and cited as a strength. Enhanced support for collaboration between data integration developers and data stewards facilitates synergy between data integration and information governance processes. The vision of an SAP real-time data platform leverages SAP Hana's in-memory computing performance and extends support for logical data warehouse architectures and big data initiatives.
  • Market presence and growth: As a large and incumbent (in many tens of thousands of enterprises) provider of applications and analytics solutions, SAP can naturally capture significant revenue in this market by leveraging its broader customer base. Its success in doing so is reflected in above-average revenue growth in the data integration tool market, as well as an increased awareness and skills base for customers to leverage.
  • Balance of emphasis in market messaging: Concerns about the emphasis of SAP's offerings becoming tightly attuned to integrating with SAP Hana caused some customer perceptions that there has been reduced emphasis on enhancing SAP's data integration tooling for non-SAP environments. Agnostic data integration capabilities are key to customers that are integrating SAP with non-SAP data sources and seeking ongoing support for data delivery between non-SAP environments.
  • Integration across product set: Despite good support for each of the main data integration styles, references cite difficulties in integrated implementations of SAP's offerings across its product portfolio. Difficulties with integrated usage of separate multiple products, such as data federation technology from BI products, SAP Data Services and SAP NetWeaver Process Orchestration, are cited as challenges. The introduction of a unified business glossary between SAP Data Services and SAP Sybase PowerDesigner is aimed at enhancing metadata management and modeling support.
  • Customer experience: While perceptions on the functionality of SAP's data integration tooling are generally positive, reference feedback indicates a decline in the quality of overall nonproduct aspects of customer experiences. Customers of SAP's data integration tools continue to express frustration with processes for obtaining product support, and the quality and consistency of support services. SAP has made efforts to expand support forums and incident management workflow, which will require continued attention to customer desire for improvements in the usability of the support portal, availability of experienced professional services, ease of product setup, and technical help for product updates, fixes and incident resolutions.


Located in Cary, North Carolina, SAS offers the following data integration products: Data Management Platform, Federation Server and SAS/Access. The vendor's customer base for this product set is estimated at more than 13,000 companies.
  • High functionality and wide connectivity: During the past three to four years, with SAS's focus on enabling interoperability among its data integration tooling products, combined with solid metadata and a wide array of available skills, the vendor's customers report that the flexibility of the tools is easily leveraged for small projects or enterprise deployments. Customers use phrases like "the Swiss Army knife" of data integration, "high self-service level" and "simplicity" to describe their experience. Also included is a Pig library with prebuilt transformations and ODBC access to Hive for Hadoop support that permits incorporating Hadoop data in transformation jobs and in support of MapReduce processing.
  • Implementation, support and product quality excellence: Reference customers report that technical support, both in presales and postimplementation, is exceptional. They specifically mention depth of knowledge regarding the products, application of vertical industry knowledge and expertise when rendering support. When combining product knowledge, industry experience, and expertise in support and professional services, customers feel significant confidence in engaging SAS. Customers also report that account management includes account executives who are knowledgeable of internal SAS expertise, and that they gain access to focused professional support from SAS when particularly difficult issues emerge, with subsequent success in dealing with those issues.
  • Solid metadata development and utilization: SAS has a highly integrated data profiling capability that can interact with data transformation processes. This provides the ability to build in job control that is based on analyzing incremental data as it moves through the data integration process, and to alert architects and users that significant data issues may exist in load jobs and actually automate the suspension or termination of those jobs. It keeps bad data out of the analysis. SAS also provides entity and object modeling, reverse engineering, and the development of models from data profiling. The vendor has added Web viewers that can be embedded into analytics applications to enable viewing of lineage, profiles, quality metrics and relational integrity management in the data. Another application of metadata is found in the data remediation functionality, which highlights data issues, creates alerts and manages workflows to address issues.
  • Diversity of usage scenarios: While SAS provides functionality commonly required for data integration activities, implementations reflect bias toward analytics-oriented scenarios that appear to be at odds with the broadening range of use cases exhibited in this market. Although deployments of SAS's data integration tools reflect its strategy and experience base being rooted in analytics, narrower use scenarios relative to leaders in this market potentially puts SAS at a competitive disadvantage. This is further evidenced by its data integration tool revenue growth being less than the market average.
  • Cost and deployment complexity: A significant number of references continue to report issues regarding the cost of SAS solutions. In addition, the large number of products makes licensing, contracting and total cost of the solutions difficult to address. Customers expressed concerns with cost escalation due to implementations of multiple products to achieve a range of data integration functionality, and cited desires for simpler ways to achieve integrated deployment across SAS's product set, where such desires parallel SAS's current state of product integration efforts.
  • Difficulty of identifying skilled personnel: Customers report a general lack of knowledge of SAS tools in the marketplace and that it is difficult to find skilled personnel. Reports of slow performance can even be attributed to this, with customers reporting that insufficient infrastructure and an inability to tune the processes are most likely culprits when performance and throughput issues actually emerge.


Located in Woodcliff Lake, New Jersey, Syncsort offers DMExpress. The vendor's customer base for this product is estimated at more than 1,200 companies.
  • Price point and usability of core functionality: Adoption of Syncsort in the data integration tool market is fueled by demands for tools with a short time to implementation and targeted functionality, with ETL capabilities at the core. Strong performance for ETL workloads, lower TCO compared with market leaders and ease of use are cited as key points of value for references selecting DMExpress. The low learning curve for implementation, customization and administration are additional drivers for market interest. The latest release of DMExpress (branded as DMX), with new Hadoop-based offerings (DMX-h ETL Edition and DMX-h Sort Edition), expands support for enabling the designs of data integration processes to be deployed on Hadoop. DMX-h takes advantage of Syncsort's recent contribution to Apache Hadoop, which provides native integration with MapReduce, added mainframe connectivity, and ETL and sort processes that can be deployed within Hadoop.
  • Customer relationship and track record: Syncsort offers a high quality of service and support, and many customers identify product technical support and their overall relationship with the vendor as positives. Customer service characteristics such as custom support, willingness to accept product enhancement suggestions (that do get included in the offerings), technical support knowledge and incident follow-through, are cited as key factors for the close relationships customers have with Syncsort. With an established track record in high-performance data processing, and a loyal customer base, Syncsort has a solid foundation on which to grow its market presence.
  • Applicability of usage scenarios: Deployments of Syncsort largely reflect support for BI and analytics, while there is broader usage for addressing operational data consistency, data migration and interenterprise data sharing. Syncsort's implementations are recognized for resolving performance bottlenecks in ETL processes, such as fast joins between very large tables with flat files, efficient usage of hardware resources when scaling with data volume growth and optimization of bulk/batch processing. New Hadoop-based offerings and a library of use case accelerators enhance Syncsort's competitive alignment to capitalize on big data requirements for implementation of common ETL use cases in Hadoop.
  • Breadth of functionality and usage experience: Although partnerships with vendors that offer extended functionality (for example, Attunity for CDC and Trillium Software for data quality) allow Syncsort to position itself for broader demand, its predominant capabilities remain very ETL-centric. Syncsort faces the risk of competitive disadvantage for not addressing a broad range of data integration styles. Requirements for non-bulk/batch-oriented data delivery are increasing, as reflected in the market as well as in Syncsort's reference customers looking to address data integration activities beyond ETL functionality. Feedback from tool usage indicates that interfaces appear dated, compared with some competitive products, and this is a factor that limits user satisfaction. Syncsort has started a phased approach to upgrade user interfaces with its first delivery via the recent release.
  • Synergy with related data management capabilities: While Syncsort continues to add metadata capabilities with each new release, reference customers continue to cite metadata management as an area of relative weakness. In particular, with Syncsort's expansion into big data environments, the increased distribution of information assets and the complexity of such environments mean that metadata discovery, modeling and dynamic use of metadata to drive runtime execution of data integration workloads will be critical. Syncsort's lack of data quality support represents a gap relative to the demand trend for synergistic deployment of data integration and data quality capabilities.
  • Guidance and support for best practices: Increased adoption is generating dissatisfaction with the lack of self-help references and methodologies to provide implementation guidance. Concerns cited regarding weaknesses in documentation reflect the growing complexity in the tool's usage scenario; hence, it is raising expectations of implementation support and the desire for readily accessible self-help resources and practices. Syncsort has begun addressing these concerns by investing in additional resources to deliver more-detailed documentation. Results so far include a knowledgebase with over 100 articles, an active user community, specific use case accelerators with videos to aid deployments and a redesigned company website.


Located in Los Altos, California, and Suresnes, France, Talend offers the following data integration products: Talend Open Studio for Data Integration, Talend Open Studio for Big Data and Talend Enterprise Data Integration. The vendor's customer base for this product set is estimated at more than 3,000 companies.
  • Relevant capabilities and integration of components: Talend offers capable bulk/batch data integration capabilities that have reached a level of maturity suitable for a significant portion of the market. Ancillary functionality comprising data quality, MDM, business process management and an enterprise service bus are well-integrated, affording customers the capability to support a broader range of data management initiatives if they desire. Talend now focuses heavily on Hadoop and other NoSQL data sources, attempting to capitalize on the contemporary excitement around big data via expanded capabilities for generating MapReduce code, interacting with Hive, and integration with emerging database technologies such as Cassandra and MongoDB. The product road map also includes an increased emphasis on public cloud deployments via Amazon Elastic Compute Cloud (Amazon EC2).
  • Cost model, flexibility and time to value: Reference customers generally report ease of use and speed of deployment as strengths of Talend's technology. They also consider the configurability of Talend's tools to be flexible enough to adapt to the business requirements of data integration processes. The availability of artifacts built by Talend's developer and user communities has contributed to high developer productivity. Most Talend customers are attracted to the tool because of its low price relative to most competitors. The combination of the free Open Studio for Data Integration product and modest subscription pricing for Enterprise Data Integration represents an attractive option for customers seeking lower-cost options, and continues to generate positive customer perceptions of value relative to cost.
  • Increasing traction and mind share: As a result of its attractive pricing model, increasing maturity of functionality (predominantly for ETL workloads) and significant vendor investments in marketing, Talend has enjoyed significant growth of its customer base during the past 12 months. The vendor appears with increasing frequency on the shortlists of organizations evaluating data integration tools. While not selected as an enterprise standard in larger organizations as often as most of its competition, Talend is regularly seen augmenting implementations of data integration capabilities where customers are budget-constrained.
  • Uneven emphasis for all data delivery styles: When focused toward data integration use cases, Talend's tools are predominantly deployed for bulk/batch-oriented data delivery, and are used much less frequently for real-time and granular data flow and message-oriented data delivery. The vendor's Data Services functionality provides basic support for data federation/virtualization, but it will need to deliver richer capabilities in light of the rapid increase in interest in this style of data integration to support real-time analytics scenarios and emerging logical data warehouse architectures.
  • Primary focus on technical developer role: Given its open-source roots, Talend appeals mainly to the technical developer community and has less mind share with IT management and application and business process owners. This creates a challenge for Talend, because its major competition has a high level of visibility with those roles, and, therefore, has a greater chance of capturing investments in information management technologies to which such roles are now leading.
  • Customer support and service experience: Despite a positive perception of the capabilities and value of the technology relative to the cost, Talend references continue to report challenges with quality of product technical support, training, documentation and professional services. Reference customers continue to report challenges with version upgrades, too many fixes/patches and bugs in new versions — although it must be noted that a portion of these customers are not running the latest versions of Talend's technology. Talend continues to work on these issues through ongoing improvements in its testing and quality assurance processes, as well as with more-formalized and documented processes and timelines for release management. In addition, despite the large developer community touted by the vendor, the limited availability of skills in Open Studio and Enterprise Data Integration in the market are cited by customers as challenges.

Vendors Added or Dropped

We review and adjust our inclusion criteria for Magic Quadrants and MarketScopes as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant or MarketScope may change over time. A vendor appearing in a Magic Quadrant or MarketScope one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. This may be a reflection of a change in the market and, therefore, changed evaluation criteria, or a change of focus by a vendor.


  • Adeptia
  • Composite Software


  • No vendors were dropped from this Magic Quadrant.
  • Information Builders-iWay Software now appears as Information Builders.
  • Pervasive Software now appears as Actian-Pervasive Software.
  • SAS-DataFlux now appears as SAS.

Inclusion and Exclusion Criteria

To be included in this Magic Quadrant, vendors must possess within their technology portfolio the subset of capabilities identified by Gartner as the most critical from within the overall range of capabilities expected of data integration tools. Specifically, vendors must deliver the following functional requirements:
  • Range of connectivity/adapter support (sources and targets): Native access to relational DBMS products, plus access to nonrelational legacy data structures, flat files, XML and message queues
  • Mode of connectivity/adapter support (against a range of sources and targets): Bulk/batch and CDC
  • Data delivery modes support: At least two modes among bulk/batch (ETL-style) delivery, federated views, message-oriented delivery or data replication
  • Data transformation support: At a minimum, packaged capabilities for basic transformations (such as data type conversions, string manipulations and calculations)
  • Metadata and data modeling support: Automated metadata discovery, lineage and impact analysis reporting, ability to synchronize metadata across multiple instances of the tool, and an open metadata repository, including mechanisms for bidirectional sharing of metadata with other tools
  • Design and development support: Graphical design/development environment and team development capabilities (such as version control and collaboration)
  • Data governance support: Ability to interoperate at a metadata level with data-profiling and/or data quality tools
  • Runtime platform support: Windows, Unix or Linux operating systems
  • Service enablement: Ability to deploy functionality as services conforming to SOA principles
In addition, vendors had to satisfy the following quantitative requirements regarding their market penetration and customer base:
  • They must generate at least $20 million of annual software revenue from data integration tools or maintain at least 300 maintenance-paying customers for their data integration tools.
  • They must support data integration tool customers in at least two of the major geographic regions (North America, Latin America, Europe, the Middle East and Africa, and the Asia/Pacific region).
We excluded vendors that focus on only one specific data subject area (for example, the integration of customer data only), a single industry, or only their own data models and architectures.
Many other vendors of data integration tools exist beyond those included in this Magic Quadrant. However, most do not meet the above criteria and, therefore, we have not included them in our analysis. Market trends during the past three years indicate that organizations want to use data integration tools that provide flexible data access, delivery and operational management capabilities within a single vendor solution. Excluded vendors frequently provide products to address one very specific style of data delivery (for example, data federation only) and cannot support other styles. Others provide a range of functionality, but operate only in a specific technical environment. Still others operate only in a single region or support only narrow, departmental implementations. Some vendors meet all the functional, deployment and geographic requirements, but are very new to the data integration tool market, and have limited revenue and few production customers.
The following vendors are sometimes considered by Gartner clients, along with those appearing in this Magic Quadrant, when deployment needs match their specific capabilities (this list also includes recent market entrants with relevant capabilities and is not intended to be comprehensive):
  • Ab Initio, Lexington, Massachusetts ( — Offers an application development toolbox (Co>Operating System) and component library for metadata management and data integration.
  • Alebra Technologies, New Brighton, Minnesota ( — Offers Parallel Data Mover for cross-platform file and database copying and sharing.
  • Apatar, Walnut, California ( — Provides open-source data integration tools focused on ETL and data synchronization scenarios.
  • Arbutus Software, Burnaby, British Columbia, Canada ( — Provides solutions for mainframe legacy data connectivity and access, in support of data integration and other use cases.
  • Astera Software, Simi Valley, California ( — Provides ETL, CDC and B2B data integration capabilities via the Centerprise Data Integrator product.
  • Ataccama, Stamford, Connecticut, and Prague, Czech Republic ( — Provides bulk loaders for industry standard databases management systems, such as Oracle DBMS and Microsoft SQL Server.
  • Attunity, Burlington, Massachusetts ( — Offers a range of data-integration-oriented products, including adapters (Attunity Connect), CDC (Attunity CDC), replication (Attunity Replicate), data federation (Attunity Federate) and data movements involving cloud-based data structures (Attunity CloudBeam) for various database/file types.
  • Axway, Phoenix ( — Offers software and services, such as B2B data integration capabilities in support of various data sources, including variants of XML and EDI.
  • BackOffice Associates, South Harwich, Massachusetts ( — Offers services and technology; the Data Stewardship Platform provides data integration capabilities for data migrations, with a focus on SAP and other ERP environments. Under the HiT Software brand, the vendor offers database replication (DBMoto), database-to-XML transformation and mapping (Allora), and DB2 connectivity products.
  • BIReady, New York and Langbroek, the Netherlands ( — Offers a dynamic model resolution tool for rationalizing, deploying and populating analytics models, coupled with a data integration engine for transformations between models.
  • C3 Business Solutions, Melbourne, Australia ( and — Offers services and technology through a simplified set of tools for consolidating data, validating data and acquiring data from sources, including Excel, Access, comma-separated values (CSV), and fixed-width and XML-standard data formats.
  • CDB Software, Houston ( — CDB/Delta provides CDC and replication capabilities for IBM DB2 on the z/OS platform.
  • DataRoket, Washington, D.C. ( — Offers ETL and data federation capabilities via the DataRoket product suite.
  • DataStreams, Seoul, Korea ( — Provides capabilities for ETL, CDC and near-real-time integration of data via a range of offerings, including TeraStream and DeltaStream.
  • Datawatch, Chelmsford, Massachusetts ( — The Datawatch Data Pump product provides ETL functionality and support for extracting data from report text, PDF files, spreadsheets and other less-structured data sources.
  • DBSync, Brentwood, Tennessee ( — Offers the dbsync integration platform for integration of data between databases and applications, via on-premises and on-demand models.
  • Dell Boomi, Berwyn, Pennsylvania ( — A business unit of Dell, Boomi provides technology for integration of data to and between SaaS-based applications and data sources.
  • Denodo Technologies, Palo Alto, California, Madrid and London ( — The Denodo Platform provides data federation/virtualization and mashup enablement capabilities for joining structured data sources with data from websites, documents and other less-structured repositories.
  • DFI, Co Dublin ( — Positioned as a data and content fusion technology, the Infinity solution supports federated approaches to data integration.
  • Diyotta, Charlotte, North Carolina ( — Focuses on extraction, loading, transformation (ELT)-style workloads leveraging parallel distributed processing architectures and database appliances, via the Diyotta Data Integration Suite.
  • Elastic Intelligence, Menlo Park, California ( — The Connection Cloud supports applications or tools to connect with SaaS data sources using SQL and offers capability for federating cloud data sources to enable access from a single virtualized view.
  • ETI, Austin, Texas, a Versata Application Development company ( and — The ETI solution has a code generation architecture focused on bulk/batch-oriented data movement.
  • ETL Solutions, Bangor, U.K. ( — Transformation Manager provides a metadata-driven toolset for the authoring, testing, debugging and deployment of various data integration requirements.
  • Extol, Pottsville, Pennsylvania ( — Extol Business Integrator (EBI) enables data and application integration involving heterogeneous environments, aimed at supporting usage in business-to-business, application, data and cloud integration.
  • Gamma Soft, Ivry-sur-Seine, France ( — Supports CDC and data replication for various heterogeneous data source types via the data'distribution product.
  • GSS Group, Markham, Ontario, Canada ( — Offers Vigilance XPress, a Web-based solution for SQL Server data marts supporting Microsoft's .NET Framework, and enabling data extraction from various ERP and DBMS sources.
  • GT Software, Atlanta ( — The Ivory Suite product line supports connectivity to, and integration with, mainframe-based data sources of various types.
  • HVR Software, Amsterdam, the Netherlands ( — Offers the HVR Realtime Data Integration product supporting CDC, propagation and replication patterns against various data source and platform types.
  • Innovative Routines International (The CoSort Co., Melbourne, Florida ( — Fast Extract and SortCL tools provide for the rapid unloading and transformation of data in bulk/batch and CDC propagation across DBMSs and flat files to address data manipulation in supporting requirements such as ETL and big data.
  • Irion, Turin, Italy ( — Supports connectivity to DBMSs and mainframe files, and the creation of federated views of data from heterogeneous sources in and outside the organization as part of a data quality governance framework.
  • iZenda, Atlanta ( — Offers iZenda Fusion providing data federation/virtualization capabilities that support real-time data access to diverse data sources for analytics uses.
  • Javlin, Arlington, Virginia ( and — Offers the CloverETL product for building, deploying and monitoring data integration processes in support of analytics and embedded use in business applications.
  • Jitterbit, Oakland, California ( — Offers software through on-premises and cloud-based models, with a focus on application integration (event- and message-based) and data integration.
  • JumpMind, Columbus, Ohio ( — The open-source SymmetricDS product set offers data replication capabilities for a variety of relational DBMS environments.
  • Kapow Software, Palo Alto, California ( — Kapow Katalyst and Kapow KappZone support data integration and creation of integration workflows from data and content in on-premises and cloud-based applications, websites, big data sources and content management repositories.
  • Kinetic Networks, San Francisco ( and — Supports ETL capabilities via KETL, an open-source data integration tool.
  • Metatomix, Austin, Texas, a Versata Application Development company ( and — Offers the Metatomix ERI platform with a semantics-based approach to the creation of data services and federated views of data across multiple data sources.
  • MioSoft, Madison, Wisconsin ( — Supports data extract and transformation, with the ability to publish data to files, relational DBMS environments and messaging infrastructure through MioBDT as well as via a cloud-based platform, MioEdge.
  • Nimaya, Washington, D.C. ( — ActionBridge technology enables virtual federation of data across on-premises and SaaS-based data sources.
  • Pentaho, Orlando, Florida ( and — Provides data integration capabilities through the Pentaho Data Integration product and by leveraging the Kettle open-source project to support uses of data from diverse environments, including relational and NoSQL DBMSs, ERP applications, and big data sources.
  • Pitney Bowes Software, Stamford, Connecticut ( — The software and service division of customer communications management vendor Pitney Bowes offers capabilities for supporting bulk data movements via Sagent Data Flow and Spectrum Technology Platform.
  • Progress Software, Bedford, Massachusetts ( — The Data Integration Suite of the vendor's DataDirect product line provides data access, replication and synchronization capabilities.
  • QlikTech, Radnor, Pennsylvania ( — Offers the QlikView Expressor product based on a semantic approach to designing and managing data integration processes.
  • Quest Software, Aliso Viejo, California ( — Acquired by Dell in 3Q12, Quest Software's SharePlex provides real-time replication support for Oracle DBMS environments and is aimed primarily at high-availability applications.
  • Red Hat, Raleigh, North Carolina ( and — The Teiid products support the creation of data models and model-driven federated views of data.
  • RedPoint, Wellesley Hills, Massachusetts ( — RedPoint Data Management provides bulk/batch-style data movements along with prebuilt tooling for address standardization and correction to offer combined support of data integration and data quality efforts.
  • Relational Solutions, Westlake, Ohio ( — The BlueSky Integration Studio provides ETL capabilities in a simplified, low-cost toolset that runs in the Windows environment.
  • Safe Software, Surrey, British Columbia, Canada ( — The Feature Manipulation Engine (FME) technology platform delivers ETL capabilities for spatially oriented data sources commonly used in geographic information system applications.
  • Scribe, Manchester, New Hampshire ( — The Scribe Insight product provides data migration and integration for supporting deployments of business applications, with a focus on Microsoft Dynamics. Scribe Online supports integration involving cloud-based data.
  • Sesame Software, Los Angeles ( — Offers the Relational Junction product suite for synchronization of data between popular packaged and SaaS applications, with a focus on ETL-oriented patterns of integration.
  • SnapLogic, San Mateo, California ( — Offers real-time and federated integration of data, with a focus on diverse data sources, including SaaS- and cloud-based sources, and via Web-oriented architectural approaches.
  • Software AG, Darmstadt, Germany ( — The CentraSite product provides data and metadata federation capabilities, and is geared toward SOA deployments. Software AG's Integration Platforms enable process-oriented integration capabilities.
  • SQData, Addison, Texas ( — The SQData product line provides data replication, CDC and ETL functionality focused on delivering mainframe data sources and popular relational DBMSs.
  • Stone Bond, Houston ( — Supports both federated/virtualized data integration and physical data movement via the Enterprise Enabler technology set.
  • Sypherlink, Worthington, Ohio, a subsidiary of Saama Technology ( — Provides metadata discovery and mapping via Harvester, and access to data sources for the creation of integrated views via Harvester Integrator.
  • Tervela, Acton, Massachusetts ( — Tervela Data Fabric supports capturing, sharing and distributing data from enterprise and cloud data sources for analytics uses enabling low-latency data movements.
  • Vision Solutions, Irvine, California ( — Real-time database replication functionality is provided by the Double-Take Share product.
  • WhereScape, Portland, Oregon ( — WhereScape RED enables the rapid creation and maintenance of data warehouses, including ETL functionality.

Evaluation Criteria

Ability to Execute

Gartner analysts evaluate technology providers on the quality and efficacy of the processes, systems, methods and/or procedures that enable IT providers' performance to be competitive, efficient and effective, and to positively impact revenue, retention and reputation. Ultimately, technology providers are judged on their ability to capitalize on their vision, and their success in doing so.
We evaluate vendors' Ability to Execute in the data integration tool market by using the following criteria:
  • Product/Service. How well the vendor supports the range of distinguishing data integration functionality required by the market, the manner (architecture) in which this functionality is delivered and the overall usability of the tools. Product capabilities are critical to the success of data integration tool deployments and, therefore, receive a high weighting.
  • Overall Viability. This refers to the magnitude of the vendor's financial resources and the continuity of its people and technology, which affect the practical success of the business unit or organization in generating business results.
  • Sales Execution/Pricing. This refers to the effectiveness of the vendor's pricing model, and the effectiveness of its direct and indirect sales channels. This criterion is weighted high due to the sustained scrutiny on cost issues and the highly competitive nature of this market.
  • Market Responsiveness and Track Record. This is the degree to which the vendor has demonstrated the ability to respond successfully to market demand for data integration capabilities over an extended period, and how well the vendor acted on the vision of prior years.
  • Marketing Execution. This is the overall effectiveness of the vendor's marketing efforts, which impacts its mind share, market share and account penetration. It also refers to the ability of the vendor to adapt to changing demands in the market by aligning its product message with new trends and end-user interests.
  • Customer Experience. This refers to the level of satisfaction expressed by customers with the vendor's product support and professional services, their overall relationship with the vendor, and their perceptions of the value of the vendor's data integration tools relative to costs and expectations. In this iteration of the Magic Quadrant, we have retained a weighting of high for this criterion, to reflect buyer's continued scrutiny of these considerations as a result of economic conditions and budgetary pressures. Analysis and rating of vendors against this criterion is driven directly by responses from customers that participated in the reference customer survey that Gartner conducted as part of the process of developing this Magic Quadrant.
Table 1. Ability to Execute Evaluation Criteria
Evaluation Criteria
Overall Viability (Business Unit, Financial, Strategy, Organization)
Sales Execution/Pricing
Market Responsiveness and Track Record
Marketing Execution
Customer Experience
No rating
Source: Gartner (July 2013)

Completeness of Vision

Gartner analysts evaluate technology providers on their ability to convincingly articulate logical statements about current and future market direction, innovation, customer needs, and competitive forces, as well as how they map to Gartner's position. Ultimately, technology providers are assessed on their understanding of the ways that market forces can be exploited to create opportunities.
We assess vendors' Completeness of Vision for the data integration tool market by using the following criteria:
  • Market Understanding. This is the degree to which the vendor leads the market in recognizing opportunities represented by trends and new directions (technology, product, services or otherwise), and its ability to adapt to significant market inertia and disruptions. Given the dynamic nature of this market, this criterion receives a weighting of high.
  • Marketing Strategy. This refers to the degree to which the vendor's marketing approach aligns with and/or exploits emerging trends and the overall direction of the market.
  • Sales Strategy. This refers to the alignment of the vendor's sales model with the ways in which customers' preferred buying approaches will evolve over time.
  • Offering (Product) Strategy. This assesses the degree to which the vendor's product road map reflects demand trends in the market, fills current gaps or weaknesses, and includes developments that create competitive differentiation and increased value for customers. In addition, given the requirement for data integration tools to support diverse environments from a data domain, platform and vendor mix perspective, we assess vendors on the degree of openness of their technology and product strategy. With the growth in diversity of data and environments involved in data integration initiatives, this criterion receives a weighting of high.
  • Business Model. This refers to the overall approach the vendor takes to execute its strategy for the data integration tool market.
  • Vertical/Industry Strategy. This refers to the degree of emphasis the vendor places on vertical solutions, and the vendor's depth of vertical market expertise.
  • Innovation. This refers to the degree to which the vendor demonstrates creative energy in the form of enhancing its practices and product capabilities, as well as introducing thought-leading and differentiating ideas and product plans that have the potential to significantly extend or reshape the market in a way that adds real value for customers. Given the pace of expansion of data integration requirements and the highly competitive nature of the market, this criterion receives a weighting of high.
  • Geographic Strategy. This refers to the vendor's strategy for expanding its reach into markets beyond its home region/country, and its approach to achieving global presence (for example, its direct local presence and use of resellers and distributors).
Table 2. Completeness of Vision Evaluation Criteria
Evaluation Criteria
Market Understanding
Marketing Strategy
Sales Strategy
Offering (Product) Strategy
Business Model
Vertical/Industry Strategy
Geographic Strategy
Source: Gartner (July 2013)

Quadrant Descriptions


Leaders in the data integration tool market are front-runners in the convergence of single-purpose tools into an offering that supports a range of data delivery styles. These vendors are strong in the more traditional data integration patterns. They also support newer patterns and provide capabilities that enable data services in the context of SOA. Leaders have significant mind share in the market, and resources skilled in their tools are readily available. These vendors establish market trends, to a large degree, by providing new functional capabilities in their products, and by identifying new types of business problems to which data integration tools can bring significant value. Examples of deployments that span multiple projects and types of use cases are common among Leaders' customers.


Challengers are well-positioned in light of the key trends in the data integration tool market, such as the need to support multiple styles of data delivery. However, they may not provide a comprehensive breadth of functionality, or may be limited to specific technical environments or application domains. In addition, their vision may be hampered by the lack of a coordinated strategy across the various products in their data integration tool portfolio. Challengers can vary significantly with regard to their financial strength and global presence. They are often large players in related markets that have only recently placed an emphasis on data integration tools. Challengers generally have substantial customer bases, although implementations are often of a single project nature, or reflect multiple projects of a single type (for example, all ETL-oriented use cases).


Visionaries have a solid understanding of emerging technology and business trends, or a position that is well-aligned with current demand, but they lack market awareness or credibility beyond their customer base or a single application domain. Visionaries may also fail to provide a comprehensive set of product capabilities. They may be new entrants lacking the installed base and global presence of larger vendors, although they could also be large, established players in related markets that have only recently placed an emphasis on data integration tools. The growing emphasis on aligning data integration tools with the market's demand for interoperability of delivery styles, convergence of related offerings (such as data integration and data quality tools), metadata modeling and support for emerging analytics environments, among other things, is creating fresh challenges for which vendors must demonstrate vision.

Niche Players

Niche Players have gaps in both their Completeness of Vision and Ability to Execute, often lacking key aspects of product functionality and/or exhibiting a narrow focus on their own architectures and installed bases. These vendors have little mind share in the market and are not recognized as proven providers of data integration tools for enterprise-class deployments. Many Niche Players have very strong offerings for a specific range of data integration problems (for example, a particular set of technical environments or application domains) and deliver substantial value for their customers in that segment.


Data integration is central to enterprises' information infrastructure. Enterprises pursuing the frictionless sharing of data are increasingly favoring technology tools that are flexible in regard to time-to-value demands, integration patterns, optimization for cost and delivery models, and synergies with data management programs.
Demand trends for enterprises to modernize their information infrastructure are fueling the emergence of data management strategies that draw on a comprehensive range of improved data integration functions and prompting users to seek data integration tools that meet their evolving requirements. Data integration capabilities are essential if data is to be shared across all organizational and system boundaries, fueling interests of a data integration hub as an enterprise competency.
Data integration offerings are emphasized to support comprehensive ways to operate across data environments, using diverse data delivery styles and an extended focus toward a model-driven approach that leverages common metadata across an integrated technology portfolio. In addressing critical components of enabling information management, data integration is an integral discipline — from assisting organizations in understanding the meaning and value of information assets to exposing and sharing them in a variety of formats and context.
In enabling information services that are necessary, tool capabilities are extending its focus on flexible latency with a mix of data delivery optimization to meet data availability requirements. IT leaders will need to anticipate and include real-time characteristics needed in their data integration architectures. Vendors' tools are exhibiting enhanced characteristics in data integration architecture, with deepened integration between bulk/batch delivery and granular, low-latency data capture and propagation.
Overlaps in some areas of data integration and related markets and disciplines represent opportunities for IT leaders to pursue multidisciplinary information capabilities in a synergistic way. Data integration functions are driven to operate synergistically with data quality, MDM, application integration, in-memory infrastructure, cloud models, and preconfigured or purpose-built appliances and platforms for data management.
At the same time, IT leaders continue to emphasize requirements for high-quality customer service and support, and are extending implementations beyond analytics-related uses to support operational data consistency, data migration, cloud-related integration and data services in SOA and big data initiatives.
The competitive landscape reflects vendors' pursuit of a more comprehensive offering strategy to support a broad range of use cases and to capitalize on new demand. IT leaders are demanding synergy between functions, performance and scalability in data integration tools, so that they operate well with the same vendor's technology stack and, increasingly, interoperate across data management infrastructures.
As buyers seek to address data integration as a critical aspect of a coherent information management capability, the need to integrate disparate data sources and new data types into a cohesive and usable set of information will continue to grow, with data integration capabilities becoming a critical part of an information capabilities framework.

Market Overview

The discipline of data integration comprises the practices, architectural techniques and tools for achieving consistent access to, and delivery of, data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes. Data integration capabilities are at the heart of the information capabilities framework (see "Information Management in the 21st Century" and "The Information Capabilities Framework: An Aligned Vision for Information Infrastructure") and will power the frictionless sharing of data across all organizational and system boundaries.
Pressures grow in this market as vendors are challenged to address demand trends for innovation with the ability to enhance traditional practices and to introduce new models and practices. Demand trends in 2013 are requiring vendors to increase flexibility in approaching comprehensive data integration needs, and demonstrating alignment to expectations on time to deployment, range of data integration patterns, sentiment for cost and delivery models, and synergy with a broad set of data management initiatives. Business imperatives to confront new information challenges are driving the need for a realignment of technology vision in this market. Meanwhile, IT leaders continue to emphasize requirements for high-quality customer service and support, and for extending implementations beyond analytics-related uses to support operational data consistency, data migration, cloud-related integration and data services in SOA initiatives.
Gartner estimates that the data integration tool market was slightly over $2 billion at the end of 2012, an increase of 7.4% from 2011. This market is seeing an above-average growth rate of the overall enterprise software market, as data integration continues to be considered a strategic priority by organizations. Ongoing interests and investments are demonstrated as organizations engage a diversity of data integration problem types and emergent demands that must be comprehensively addressed. A projected five-year compound annual growth rate of approximately 9.7% will bring the total to more than $3.2 billion by 2017 (see "Forecast: Enterprise Software Markets, Worldwide, 2012-2017, 2Q13 Update").
The market for data integration tools has exhibited substantial demands for technologies that offer breadth of functionality, high performance and the scalability needed to support enterprise-scale implementations. Buyers in this market continue to expand their usage and seek vendor technologies to serve a range of data integration capabilities applicable to a variety of use cases. This competitive landscape reflects vendor pursuit of a more comprehensive set of product offerings that together form their data integration tool portfolio, for supporting a broad range of uses and capitalizing on new demand.
Changes in the positioning of vendors in this iteration of the Magic Quadrant are driven not only by vendors' activities in delivering new product capabilities, but also by their degree of success in targeting contemporary demands.
Strategy in Enterprises to Make Data Integration Central to the Information Infrastructure
With the ongoing evolution of the data integration tool market, enterprises' need to improve the flexibility of their information infrastructure is fueling the emergence of data management strategies that draw on a comprehensive range of improved data integration functions, and is prompting users to seek data integration tools that meet their evolving requirements. Businesses' requirements to confront new information challenges are driving a realignment of technology vision in this market. In a move away from meeting data integration requirements with disparate interfaces and tools, forward-thinking enterprises are beginning to pursue the architectural concept of a data integration hub capable of managing the exchange of entity information — such as in relating to customers, products or suppliers — and transactional context (see "Data Integration Hubs: Drivers, Benefits and Challenges of an Increasingly Popular Implementation Approach"). This need for a set of shared and coordinated data integration tooling is further escalated by requirements in big data initiatives for integrating an extreme level of information from emerging sources (including unstructured data or content) and combining disparate data sources and new data types into a usable, cohesive set. The increasing activity among data integration technology providers is evident in tool enhancements to address trends and demand and to provide early offerings that take advantage of external parallelization techniques, such as Hadoop distributions and MapReduce-oriented algorithms. A growing emphasis on aligning strategy and future direction in terms of market understanding, offering strategy and adaptability to capitalize on new challenges is driving a renewed vision and focus among providers.
Rationalization of Tools Intensifies in Enterprises for Cost and IT Resource Optimization
Gartner's interactions with clients indicate an escalating desire in organizations to reduce the number of tactical data integration tools with a chosen or enforced enterprise standard. These organizations are recognizing their limited ability to extend data delivery approaches to join silos of information and the ongoing redevelopment of integration artifacts and components are escalating costs across the business. Standardized tools will help promote a shared-service model for data integration, improve the quality and efficiency of data integration work and potentially lower costs as enterprises improve their ability to reuse tools in a variety of business contexts. Vendors with established track records and strong leadership exhibit support for comprehensive data integration patterns, as providers of narrow-style offerings encounter limited adoption as the enterprise standard for data integration infrastructure.
Awareness Grows in Enterprises to Address the Lack of Data Integration Strategy
Pressures for amassing data to respond to business needs and changes, requirements for data delivery support, and urgencies for making data available in real time or within a minute will critically impact business agility. While data integration must be pursued with a strategic view to ensure success, many organizations at large still lack a comprehensive approach to data integration. For most organizations, pursuing and investing in data integration as a strategic and coherent enterprise capability remains an uphill justification. Addressing requirements early with the business is crucial, because it is easier to architect than to retrofit characteristics that must be present in an architecture for a multimode, multipurpose data integration environment that flexibly operates beyond conventional bulk/batch movements, to include nonbulk approaches for replication, federation and message-based integration. Data integration must be able to envision characteristics that are essential in its architecture to support a mix of latencies, for the extent of granularity and the nature of real-time demand for data delivery. Also gaining interest is the approach of service orientation to address needs for the consistent, yet flexible, delivery of data. Enterprises that are maturing in their adoption of data integration tools are emphasizing common design tooling, metadata and runtime architecture applicable across data integration efforts. The ability of vendors to understand buyers' wants and needs and to translate those into products and services will influence or enhance adoptions, as a result of the vision of how providers shape their approach to provisioning their product set.
Demand for Synergy Between Data Integration and Data Management and Application Integration Initiatives
During the past five years, more and more enterprises have demanded data integration offerings that support comprehensive ways to operate across data environments. Across data-management-related efforts, capabilities are needed for diverse data delivery styles, tightened links to data quality tools, MDM solutions and an extended focus toward a model-driven approach that leverages common metadata across a technology portfolio. In addition, overlaps in some areas of data integration and application integration represent opportunities — for IT leaders responsible for integration infrastructure — to pursue both disciplines in a synergistic way. Organic expansion of vendors' capabilities into neighboring areas, such as application integration, provides opportunities to leverage the intersection of data integration and application integration by means of tools offering capabilities in common areas to deliver shared benefits (see "Leveraging the Convergence of Application and Data Integration"). Seamless interoperability of data and application integration functionality using a unified platform is increasingly regarded as a point of value by forward-looking enterprises.
Federated and Virtual Views Gains Importance in Logical Data Warehouse Architectures
Diverse requirements for the data warehouse force changes in how data is manipulated. Evolving approaches on logical data warehouse (LDW) architectures are including implementation techniques beyond those that are repository-based (see "Understanding the Logical Data Warehouse: The Emerging Practice"). Among enterprises, this is generating wider interest in how federated views of data are becoming important for the LDW effort. The need to render data resources useful wherever they are deployed presents opportunities to use data federation and virtualization to read data in place, instead of focusing data warehousing efforts exclusively on the storage of integrated datasets in dedicated repositories. Capabilities for access-oriented data services that enable enterprises to move toward SOA are relevant for supporting the LDW's use of abstracted interfaces. Introducing federation into the mix of data delivery capabilities can enable the use of in-memory infrastructure to assimilate the distributed data of an LDW, a task that involves pushing data to a range of repository types and pulling together views across combinations of those repositories on the fly.
Reusability of Tools for Broad Applicability of Use Cases
Use cases for data integration tools are diversifying as buyers procure tools with the aim of supporting a wide range of projects and initiatives. Although data integration tools are still mainly deployed for BI, analytics and data warehousing initiatives, the growing complexity and diversity of usage scenarios is also fueling demand. Uses of federated views of data to leverage distributed enterprise data in an LDW are attracting early interest as a means of aggregating and providing data rapidly to the business. Data migrations in support of modernization and consolidation initiatives are growing, with data integration capabilities — and the related technology area of data quality — providing critical infrastructure for such efforts. As MDM programs increase in number and scope, organizations also seek to apply investments in data integration technology to these programs, to which the movement, transformation and federation of master data is fundamental. Synchronization of data between operational applications and across enterprise boundaries (between trading partners or between on-premises and cloud-based applications) also represents an area of growth. Increasingly, end-user organizations are deploying data integration services beneath, and in support of, wider SOA initiatives.
The Customer Experience of Support and Service Is a High Priority
The customer experience is increasingly important to organizations when choosing vendors in terms of overall customer service and support, pricing approaches for data integration tools, and the perception of value relative to cost models. With reduced staff and budget, and amid mounting pressure for faster and higher-quality delivery of solutions, buyers are demanding a superior customer service and support experience from their technology providers. In addition to highly responsive and high-quality technical support, customers desire direct and frequent interactions with sales teams and executives. Buyers are also focusing strongly on the availability of skills both within a provider's installed base and via system integrator partners, and of forums in which they can share experiences, lessons and solutions with their peers.

9 commentaires:

  1. I really appreciate information shared above. It’s of great help. If someone want to learn Online (Virtual) instructor lead live training in TECHNOLOGY , kindly contact us
    MaxMunus Offer World Class Virtual Instructor led training on TECHNOLOGY. We have industry expert trainer. We provide Training Material and Software Support. MaxMunus has successfully conducted 100000+ trainings in India, USA, UK, Australlia, Switzerland, Qatar, Saudi Arabia, Bangladesh, Bahrain and UAE etc.
    For Demo Contact us.
    Saurabh Srivastava
    Skype id: saurabhmaxmunus
    Ph:+91 8553576305 / 080 - 41103383

  2. I really appreciate information shared above. It’s of great help. If someone want to learn Online (Virtual) instructor lead live training in talend , kindly contact us
    MaxMunus Offer World Class Virtual Instructor led training on TECHNOLOGY. We have industry expert trainer. We provide Training Material and Software Support. MaxMunus has successfully conducted 100000+ trainings in India, USA, UK, Australlia, Switzerland, Qatar, Saudi Arabia, Bangladesh, Bahrain and UAE etc.
    For Demo Contact us.
    Sangita Mohanty
    Skype id: training_maxmunus
    Ph:(0) 9738075708 / 080 - 41103383

  3. Maxmunus Providing Free Webinar/Demo on Qlikview. Qlikview tutorial step to step process will help understanding QlikView tutorial in better way. also Qlikview tutorial pdf include each and every detail of QlikView basics for beginners.
    For Registration Contact:
    Name : Arunkumar U
    Email :
    Skype id:
    Contact No: +91- 9738507310,
    Company Website :-

  4. Maxmunus Providing Free Webinar/Demo on JBoss. JBoss tutorial step to step process will help understanding JBoss tutorial in better way. also JBoss tutorial pdf include each and every detail of JBoss basics for beginners.

    For Registration Contact:
    Name : Arunkumar U
    Email :
    Skype id:
    Contact No: +91- 9738507310,
    Company Website :-


  5. Maxmunus Providing Free Webinar/Demo on Qlikview.Qlikview tutorial step to step process will help understanding QlikView tutorial in better way. also Qlikview tutorial pdf include each and every detail of QlikView basics for beginners.
    For Registration Contact:
    Name : Arunkumar U
    Email :
    Skype id:
    Contact No: +91- 9738507310, 080-41103383
    Company Website :-

  6. awesome post presented by you..your writing style is fabulous and keep update with your blogs Informatica Online Training

  7. This blog is very useful and informative. Thanks for sharing.
    SAS Certification

  8. Thank you so much for this nice information. Hope so many people will get aware of this and useful as well. And please keep update like this.

    Big Data Consulting Services

    Data Lake Solutions

    Advanced Analytics

    Product Development Services