magic quadrant for data integration tools

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Magic Quadrant for Data Integration Tools29 July 2015 ID:G00269320

Analyst(s): Eric Thoo, Lakshmi Randall

VIEW SUMMARY

Enterprise buyers increasingly see data integration as a strategic requirement, for which theywant comprehensive data delivery capabilities, flexible deployment models, and synergies withinformation and application infrastructures. To help them make the right choice, Gartner assesses13 vendors.

Market Definition/DescriptionThe discipline of data integration comprises the practices, architectural techniques and tools forachieving consistent access to, and delivery of, data across the spectrum of data subject areasand data structure types in the enterprise — to meet the data consumption requirements of allapplications and business processes.

The market for data integration tools includes vendors that offer software products to enable theconstruction and implementation of data access and data delivery infrastructure for a variety ofdata integration scenarios. These include:

Data acquisition for business intelligence (BI), analytics and data warehousing —Extracting data from operational systems, transforming and merging that data, anddelivering it to integrated data structures for analytics purposes. The variety of data andcontext for analytics is expanding as emergent environments — such as NoSQL and Hadoopdistributions for supporting big data, in-memory DBMSs, logical data warehouse architecturesand end-user capability to integrate data (as part of data preparation) — increasinglybecome parts of the information infrastructure.

ACRONYM KEY AND GLOSSARY TERMS

BI bus iness intelligence

CDC change data capture

CRM cus tomer relationship

management

DBMS database management sys tem

EDI elec tronic data interchange

EIM enterprise information

management

ELT extrac tion, loading and

trans formation

ESB enterprise service bus

ETL extrac tion, trans formation and

loading

HDFS Hadoop Dis tributed File

Sys tem

HL7 Health Level Seven

International

iPaaS integration platform as a

service

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Sourcing and delivery of master data in support of master data management (MDM) —Enabling the connectivity and integration of the data representing critical business entitiessuch as customers, products and employees. Data integration tools can be used to build thedata access and synchronization processes to support MDM initiatives.

Data migrations/conversions — Although traditionally addressed most often via the customcoding of conversion programs, data integration tools are increasingly addressing the datamovement and transformation challenges inherent in the replacement of legacy applicationsand consolidation efforts during mergers and acquisitions.

Data consistency between operational applications — Data integration tools provide theability to ensure database-level consistency across applications, both on an internal and aninterenterprise basis (for example, involving data structures for 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 partnersand others). Data integration tools are relevant for addressing these challenges, which oftenconsist of the same types of data access, transformation and movement component found inother common use cases.

The usage of data integration tools may display characteristics not unique to one of theseindividual scenarios. Technologies in this market are required to execute many of the corefunctions of data integration, which can apply to any of the above scenarios. Examples ofresulting characteristics include:

Interoperating with application integration technology in a single solution architecture to, forinstance, expose extraction, transformation and loading (ETL) processes that extract datafrom sources as a service to be provisioned via an enterprise service bus.

Enabling data services as an architectural technique in a service-oriented architecture (SOA)context. Rather than a use of data integration per se, this represents an emerging trend fordata integration capabilities to play a role, and to be implemented within, software-definedarchitecture for application services.

Integrating a combination of data residing on-premises and in SaaS applications or othercloud-based data stores and services, to fulfill requirements such as cloud serviceintegration.

Supporting the delivery of data to, and the access of data from, platforms typicallyassociated with big data initiatives, such as Hadoop, NoSQL and cloud-based data stores.These platforms provide opportunities for distributing data integration workloads to externalparallelized processes. The emerging concept of a "data lake," where data is continuouslycollected and stored in a lightly structured NoSQL repository, poses data integrationchallenges but also opportunities to assist in the application of schemas at data read-time, ifneeded, and to deliver data to business users, processes or applications, or to use dataiteratively.

JDBC Java Database C onnec tivity

JMS Java Message Service

JSON JavaScript O bjec t Notation

LDW logical data warehouse

MDM master data management

ODBC O pen Database C onnec tivity

ODI O rac le Data Integrator

REST representational s tate trans fer

SaaS software as a service

SOA service-oriented architec ture

SOAP Simple O bjec t A ccess P rotocol

SSIS SQ L Server Integration

Services (M ic rosoft)

SWIFT Soc iety for Worldwide

Interbank Financ ial

Telecommunication

TCO total cos t of ownership

EVIDENCE

The analysis in this Magic Quadrant is based oninformation from a number of sources, including:

Extensive data on functional capabilities,customer base demographics, financial status,pricing and other quantitative attributesgained via an RFI process engaging vendorsin this market.Interactive briefings in which the vendorsprovided Gartner with updates on theirstrategy, market positioning, recent keydevelopments and product roadmap.A Web-based survey of reference customersprovided by each vendor, which captured dataon usage patterns, levels of satisfaction withmajor product functionality categories, variousnontechnology vendor attributes (such aspricing, product support and overall servicedelivery), and more. In total, 348organizations across all major regions




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iteratively.

Gartner has defined several classes of functional capability that vendors of data integration toolsprovide to deliver optimal value to organizations in support of a full range of data integrationscenarios:

Connectivity/adapter capabilities (data source and target support). The ability to interactwith a range of different types of data structure, including:

Relational databases

Legacy and nonrelational databases

Various file formats

XML

Packaged applications, such as those for CRM and supply chain management

SaaS and cloud-based applications and sources

Industry-standard message formats, such as electronic data interchange (EDI), HealthLevel Seven International (HL7) and Society for Worldwide Interbank FinancialTelecommunication (SWIFT)

Parallel distributed processing environments such as Hadoop Distributed File System(HDFS) and other NoSQL-type repositories, such as graph, table-style, document storeand key-value DBMSs

Message queues, including those provided by application integration middlewareproducts and standards-based products (such as Java Message Service)

Data types of a less structured nature, such as that associated with social media, Webclickstreams, email, websites, office productivity tools and content

Emergent sources, such as data on in-memory repositories, mobile platforms andspatial applications

Screen-scraping and/or user interaction simulations (for example, scripts to interactwith Web, 3270, VT100 and others)

Data integration tools must support different modes of interaction with this range of datastructure types, including:

Bulk/batch acquisition and delivery

Granular trickle-feed acquisition and delivery

Change data capture (CDC) — the ability to identify and extract modified data

Event-based acquisition (time-based, data-value-based, or links to application integrationtools to interact with message request/reply, publish/subscribe, and routing)

provided input on their experiences withvendors and tools in this manner.Feedback about tools and vendors capturedduring conversations with users of Gartner'sclient inquiry service.Market share estimates developed byGartner's Technology and Service Providerresearch unit.

EVALUATION CRITERIA DEFINITIONS

Ability to ExecuteProduct/Service: Core goods and servicesoffered by the vendor for the defined market.This includes current product/service capabilities,quality, feature sets, skills and so on, whetheroffered natively or through OEMagreements/partnerships as defined in themarket definition and detailed in the subcriteria.

Overall Viability: Viability includes an assessmentof the overall organization's financial health, thefinancial and practical success of the businessunit, and the likelihood that the individualbusiness unit will continue investing in theproduct, will continue offering the product and willadvance the state of the art within theorganization's portfolio of products.

Sales Execution/Pricing: The vendor's capabilitiesin all presales activities and the structure thatsupports them. This includes deal management,pricing and negotiation, presales support, and theoverall effectiveness of the sales channel.

Market Responsiveness/Record: Ability torespond, change direction, be flexible andachieve competitive success as opportunitiesdevelop, competitors act, customer needs evolveand market dynamics change. This criterion alsoconsiders the vendor's history of responsiveness.

Marketing Execution: The clarity, quality,creativity and efficacy of programs designed todeliver the organization's message to influencethe market, promote the brand and business,increase awareness of the products, and establisha positive identification with the product/brandand organization in the minds of buyers. This"mind share" can be driven by a combination of




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Data delivery capabilities. The ability to provide data to consuming applications, processesand databases in a variety of modes, including:

Physical bulk/batch data movement between data repositories, such as processes forETL or extraction, loading and transformation (ELT)

Data federation/virtualization

Message-oriented encapsulation and movement of data (via linkage with applicationintegration tool capability)

Replication of data between homogeneous or heterogeneous DBMSs and schemas

In addition, support for the delivery of data across the range of latency requirements isimportant, 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 transformationoperations of varying complexity, including:

Basic transformations, such as data-type conversions, string manipulations and simplecalculations

Transformations of intermediate complexity, such as look-up and replace operations,aggregations, summarizations, integrated time series, deterministic matching and themanagement of slowly changing dimensions

Complex transformations, such as sophisticated parsing operations on free-form text,rich media and patterns/events in big data

In addition, the tools must provide facilities for developing custom transformations and extendingpackaged transformations.

Metadata and data modeling support. As the increasingly important heart of dataintegration capabilities, metadata management and data modeling requirements include:

Automated discovery and acquisition of metadata from data sources, applications andother tools

Discernment of relationships between data models and business process models

Data model creation and maintenance

Physical-to-logical model mapping and rationalization

Ability to define model-to-model relationships via graphical attribute-level mapping

Lineage and impact analysis reporting, in graphical and tabular formats

"mind share" can be driven by a combination ofpublicity, promotional initiatives, thoughtleadership, word of mouth and sales activities.

Customer Experience: Relationships, productsand services/programs that enable clients to besuccessful with the products evaluated.Specifically, this includes the ways customersreceive technical support or account support. Thiscan also include ancillary tools, customer supportprograms (and the quality thereof), availability ofuser groups, service-level agreements and so on.

Operations: The ability of the organization tomeet its goals and commitments. Factors includethe quality of the organizational structure,including skills, experiences, programs, systemsand other vehicles that enable the organization tooperate effectively and efficiently on an ongoingbasis.

Completeness of VisionMarket Understanding: Ability of the vendor tounderstand buyers' wants and needs and totranslate those into products and services.Vendors that show the highest degree of visionlisten to and understand buyers' wants andneeds, and can shape or enhance those with theiradded vision.

Marketing Strategy: A clear, differentiated set ofmessages consistently communicated throughoutthe organization and externalized through thewebsite, advertising, customer programs andpositioning statements.

Sales Strategy: The strategy for selling productsthat uses the appropriate network of direct andindirect sales, marketing, service, andcommunication affiliates that extend the scopeand depth of market reach, skills, expertise,technologies, services and the customer base.

Offering (Product) Strategy: The vendor'sapproach to product development and deliverythat emphasizes differentiation, functionality,methodology and feature sets as they map tocurrent and future requirements.

Business Model: The soundness and logic of thevendor's underlying business proposition.

Vertical/Industry Strategy: The vendor'sstrategy to direct resources, skills and offerings tomeet the specific needs of individual market




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An open metadata repository, with the ability to share metadata bidirectionally withother tools

Automated synchronization of metadata across multiple instances of the tools

Ability to extend the metadata repository with customer-defined metadata attributesand relationships

Documentation of project/program delivery definitions and design principles in supportof requirements definition activities

A business analyst/end-user interface to view and work with metadata

Design and development environment capabilities. Facilities for enabling the specificationand construction of data integration processes, including:

Graphical representation of repository objects, data models and data flows

Management of the development process workflow, addressing requirements such asapprovals 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 theidentification of redundancies

A common or shared user interface for design and development (of diverse datadelivery styles, of data integration and data quality operations, of cloud and on-premises environments, and so on)

A business analyst/end-user interface to specify and manage mapping andtransformation logic through the use of end-user functionality for dataintegration/preparation

Support for testing and debugging

Information governance support capabilities (via interoperation with data quality,profiling and mining capabilities with the vendor's or a third party's tools). Mechanisms towork with related capabilities to help with the understanding and assurance of data qualityover time, including interoperability with:

Data profiling tools (profiling and monitoring the conditions of data quality)

Data mining tools (relationship discovery)

Data quality tools (supporting data quality improvements)

Deployment options and runtime platform capabilities. Breadth of support for thehardware and operating systems on which data integration processes may be deployed, andthe choices of delivery model — specifically:

Mainframe environments, such as IBM z/OS and z/Linux

Midrange environments, such as IBM System i or HP Tandem

meet the specific needs of individual marketsegments, including vertical markets.

Innovation: Direct, related, complementary andsynergistic layouts of resources, expertise orcapital for investment, consolidation, defensive orpre-emptive purposes.

Geographic Strategy: The vendor's strategy todirect resources, skills and offerings to meet thespecific needs of geographies outside the "home"or native geography, either directly or throughpartners, channels and subsidiaries asappropriate for that geography and market.




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Unix-based environments

Windows environments

Linux environments

On-premises (at the customer site) installation and deployment of software

Hosted off-premises software deployment (dedicated, single-tenant implementation)

Integration platform as a service (iPaaS), consumed by the customer completely "as aservice" — the vendor provides cloud infrastructure; the customer does not install andadminister the software

Cloud deployment support (requires organizations to deploy software in cloudinfrastructure)

In-memory computing environment

Server virtualization (support for shared, virtualized implementations)

Parallel distributed processing (such as Hadoop and MapReduce)

Operations and administration capabilities. Facilities for enabling adequate ongoingsupport, management, monitoring and control of the data integration processesimplemented by the tools, such as:

Error-handling functionality, both predefined and customizable

Monitoring and control of runtime processes, both via functionality in the tools andthrough interoperability with other IT operations technologies

Collection of runtime statistics to determine use and efficiency, as well as anapplication-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 andinteroperability 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 allcomponents 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/batchversus granular real-time versus federation) with minimal rework

Interoperability with other integration tools and applications, via certified interfaces,robust APIs and links to messaging support

Efficient support for all data delivery modes, regardless of runtime architecture type(centralized server engine versus distributed runtime)

The ability to execute data integration in cloud and on-premises environments, as




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appropriate, where developed artifacts can be interchanged, reused and deployedacross both environments with minimal rework

Service enablement capabilities. As acceptance of data service concepts continues to grow,so data integration tools must exhibit service-oriented characteristics and provide supportfor SOA, such as:

The ability to deploy all aspects of runtime functionality as data services (for example,deployed functionality can be called via a Web services interface)

Management of publication and testing of data services

Interaction with service repositories and registries

Service enablement of development and administration environments, so that externaltools and applications can dynamically modify and control the runtime behavior of thetools

Magic Quadrant

Figure 1. Magic Quadrant for Data Integration Tools




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Source: Gartner (July 2015)

Vendor Strengths and CautionsActian




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Based in Redwood City, California, U.S., Actian offers data integration capabilities via ActianDataConnect and Actian DataCloud. Actian's customer base for data integration tools is estimatedto number more than 6,800 organizations.

Strengths

Core capability and performance. Actian's continued focus on diverse connectivity andemphasis on industry-standard message formats enable companies to support diverse dataintegration requirements, from real-time to batch mode. Customers report Actian'sbulk/batch data delivery to be a key strength, one favored in implementations for havingstrong scalability and performance.

User productivity. The extension of functionality so that business roles can control user-defined integration mapping and data loading enables productivity gains. Actian hasextended the capabilities of DataCloud and DataConnect, which will evolve to be deliveredas managed services to further simplify customer onboarding and ease use forinterenterprise data sharing.

Customer relationship. Actian's partnering posture toward companies results in a strongcustomer experience, encompassing the presale process, the selling process, and thepostsale relationship.

Cautions

Challenges with major upgrades. Customers report challenges with upgrades betweenmajor releases. A migration utility offered by Actian, along with increased frequency ofreleases, is intended to reduce the complexity of each upgrade and ease migration efforts.

Linkage of product support with professional services. Customers would like to see betteralignment between Actian's data integration tools, along with access to implementation skillsand professional services.

Market positioning of use cases. The perceived closeness of alignment between Actian'sportfolio and analytics support requirements represents a competitive disadvantage forprospective buyers. However, customers report diverse data integration use cases inproduction.

AdeptiaBased in Chicago, Illinois, U.S., Adeptia offers the Adeptia Integration Suite and Adeptia Connect.Adeptia's customer base for this product set is estimated to number approximately 530organizations.

Strengths

Integrated product and time-to-value: Adeptia's data integration technology is offeredalongside other integration tools that provide an enterprise service bus, B2B integration and

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trading partner management — all in a single product. Customers appreciate the tightintegration of the underlying components and the ability to support rapid implementation.

Expanded applicability using cloud services. Adeptia Connect offers iPaaS functionality thatenables interenterprise data sharing, where businesses are able to publish and use dataconnectors for B2B integration. Planned enhancements to support EDI schemas, datadictionaries, mapping and prebuilt EDI connections to common applications are expected atthe end of 2015, followed by a single interface for using both iPaaS and on-premises tools.

Pricing and value. Customers view Adeptia's tools as attractively priced and as deliveringgood value, relative to the cost of tools from major competitors. Adeptia's recentstandardization of subscription-based pricing aims to simplify procurement, based on tierededitions and feature sets.

Cautions

Skills and market coverage. While Adeptia claims its products' ease of use and reduceddependence on skilled resources are differentiators, finding those skilled resources mightprove challenging for organizations trying to implement and maintain deployments as theirrequirements grow.

Learning experience. Some Adeptia customers indicate usage challenges when business-oriented users, rather than integration developers, are first learning to perform complexdata integration activities. Generally, however, Adeptia's enabling of business-user-drivenintegration tasks and overall ease of use attract buyers to 'its Web-based product — andthese are differentiating factors that the company continues to focus on.

Big data support. Overall, Adeptia's implementations and competitive activities indicatelimited traction in support of big data initiatives, which are increasingly emphasized in thismarket.

CiscoBased in San Jose, California, U.S., Cisco offers the Cisco Information Server and Cisco IntegrationPlatform. Cisco's customer base for this product set is estimated to number more than 320organizations.

Strengths

Agility and rapid time-to-value. Cisco has a strong focus on data federation/virtualization,and a well-established track record for capitalizing on the growing demand in this area.Reference customers praise Cisco's data virtualization technology for enabling agiledevelopment, and using optimization techniques such as pushing processing down to datasources, which minimizes data movement and reduces time-to-value.

Expanding product portfolio. Cisco continues to evolve its product portfolio by supportingthe logical data warehouse (LDW), integrating streaming data and Internet of Things (IoT)environments, linking with Cisco Tidal Enterprise Scheduler for data integration workflows,

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environments, linking with Cisco Tidal Enterprise Scheduler for data integration workflows,and envisaging capability for data preparation. Cisco's expanding product portfolio supportsthe objective of enabling bimodal IT and digitalization, and of providing an enhancedanalytics experience.

Customer relationship and market access. Reference customers state that Cisco isextremely responsive to customer needs and that the quality of its customer support isgood. Cisco's global reach continues to widen the availability of the data integration tools itacquired from Composite Software.

Cautions

Breadth of coverage and market resonance. Organizations seeking providers with acomprehensive range of data delivery capabilities (beyond federated/virtualized styles) oftenfind Cisco's product set to be narrow. Cisco's relatively small customer base in this marketlimits the availability of relevant skills, which at times poses a barrier to adoption. Cisconeeds to increase its market resonance on the basis of its acquired offerings from CompositeSoftware, as Cisco is not an incumbent vendor in the information management technologysector.

Synergy with data management capabilities. Although Cisco is working to improve itsmetadata support, customers are still looking for a seamless way to integrate metadataacross diverse data integration use cases. Customers are increasing their expectations forgovernance support and requiring integrated use of Cisco's data integration capability withcomprehensive data quality tools.

Deployment and diagnostic guidance. Reference customers identify diagnosis of errormessages as challenging, and require better diagnostic support and integrateddocumentation. Customers also expressed a desire for a more mature user community, forimproved access to implementation guidance and practices.

DenodoBased in Palo Alto, California, U.S., Denodo offers the Denodo Platform. Denodo's customer basefor its data integration product is estimated to number 250 companies.

Strengths

Capitalization on demand. The Denodo Platform provides data virtualization, with anestablished basis in the enabling of data abstraction capabilities for joining multistructureddata sources from DBMSs, websites, documents and a variety of repositories. Physical datamovements are supported via the Denodo Scheduler component, which delivers data fromrepository to cache, or directly to another repository. Denodo capitalizes on the increasingtraction and importance of data virtualization in the overall market for data integration tools.

Track record and partner channels. With a recognized track record in data virtualization,Denodo has built a partner network of implementers and joint-marketing vendors, includingIBM, Cloudera, Hortonworks, MicroStrategy, Tableau, SAP, MongoDB and Pivotal. A diverse

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range of software vendors license or bundle Denodo's functionality as part of their productsin support of logical abstraction and agility for analytics, big data and operational use cases.

Connectivity support and links to related integration capability. The Denodo Platformprovides broad connectivity to relational databases, prerelational legacy data, flat files, XML,packaged applications and emergent data types including Hadoop and cloud-based datasources. The Denodo Platform can receive and publish data in a variety of formats andinterfaces, including Java Database Connectivity (JDBC), Open Database Connectivity(ODBC), Java Message Service (JMS)-compliant message queues, REST and SOAP Webservices, JavaScript Object Notation (JSON), XML, portlets and SharePoint Web parts. It canalso support discovery and the use of data services.

Cautions

Breadth of coverage. Organizations seeking providers with a breadth of data delivery stylesmay find Denodo's integrated platform to have limited versatility, relative to competitors withtoolsets for diverse data delivery. Customers express a desire for easier administrativemanageability and links to related tools for data governance support.

Degree of metadata support. Reference customers identify Denodo's metadatamanagement as an area of relative weakness when enabling reusability across a growingrange of software tools and use cases. Customers increasingly look for comprehensivefunctionality and a vision for these requirements, to address the escalating number andvariety of datasets and distributed data architectures.

Availability of skills and best-practice documentation. Since Denodo has a relatively smallcustomer base, customers express concerns about a lack of adequately skilled implementersin the market. Denodo has addressed this shortcoming with additional system integrationpartners and training. Reference customers express a desire for improvements in guidanceon design architecture and documentation of best practices.

IBMBased in Armonk, New York, U.S., IBM offers the following data integration products: IBMInfoSphere Information Server Enterprise Edition (including InfoSphere Information Server forData Integration and InfoSphere Business Information Exchange), InfoSphere Federation Server,InfoSphere Data Replication, InfoSphere Information Server Enterprise Hypervisor Edition andWebSphere Cast Iron Live. IBM's customer base for this product set is estimated to number morethan 10,700 organizations.

Strengths

Depth and breadth of usage. IBM's data integration tools continue to be deployed forextensive use cases — often those of complex scale, spanning a wide range of projects andinvolving teams of various sizes.

Mind share and capitalization on market demand. IBM continues to gain traction as an

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enterprise standard for data integration infrastructure, with a strong presence in competitivebids. The linkage of data integration capability with diverse analytics support, and theembedding of IBM DataWorks (for self-service data preparation) in Watson Analytics and incloud-based data stores such as IBM dashBD, are increasing the synergy of IBM's dataintegration tools with its broader portfolio.

Versatility in enabling information infrastructure and analytics. IBM continues to focus onenabling information infrastructure modernization in its efforts to align data integration withdiverse demands for information capabilities (including data quality and governance, supportfor line-of-business users, big data, integration support in cloud adoptions and MDM). IBM'sdata integration focus is expanding applicable usage scenarios to business-facing roles byincreasing self-service capabilities and deepening the synergies between informationinfrastructure and analytics use cases, to form integrated toolsets available on a commonplatform.

Cautions

Product support and version upgrades. Customers reported difficulty with version upgradesand migrations. IBM has begun mitigating this through in-place upgrades, where downtimecan be avoided, and will continue to mitigate it by converging the timing of variousInfoSphere product releases, for better anticipation and alignment of upgrades.

Pricing model. Reference customers identify software costs and perceived total cost ofownership (TCO) as barriers to broader adoption. IBM's provision of varied licensingapproaches, such as core-, workgroup-, bundle-, subscription- and perpetual-based models,while intended to provide more procurement and pricing choices, has reportedly alsoconfused customers assessing and selecting pricing models.

Complexity of integrated use of portfolio. In general, customers expressed difficulty withintegrated deployments of IBM's data integration tools alongside other IBM products, suchas challenges associated with the integration of IBM InfoSphere DataStage with IBMBigInsights.

InformaticaBased in Redwood City, California, U.S., Informatica offers the following data integration products:Informatica Platform (including PowerCenter, PowerExchange, Data Services, Data Replication,Ultra Messaging, Big Data, B2B Data Exchange and Data Integration Hub), Vibe Data Stream, andInformatica Cloud Integration. Informatica's customer base for this product set is estimated tonumber more than 5,500 organizations. At the time of writing, Informatica has announced anagreement for it to be acquired and taken into private ownership by a company controlled by theEuropean private equity firm Permira Advisers and the Canada Pension Plan Investment Board.The acquisition awaits regulatory approval and is scheduled to be completed in 3Q15.

Strengths

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Strength of data integration functionality and synergy with portfolio. Informatica's toolscontinue to reflect a diverse range of data integration styles, usage scenarios andmultiproject deployments. Strong synergies between Informatica's data integration tools andother Informatica technologies encourage usage as an enterprise standard for a dataintegration infrastructure that links with data quality, MDM, big data, data security and cloudintegration technologies. Informatica's emphasis on supporting digital services, the IoT, andrelated analytics and data security opportunities capitalizes on trends in demand.

Broad presence and dedicated focus on, and innovation in, data management andintegration. Informatica's mind share in this market is extensive, with the highest frequencyof appearances in competitive situations. Informatica's concentration on enabling informationcapabilities aligns its application- and technology-agnostic offerings with a broad range ofestablished and emerging information infrastructures. Informatica's v10 release, planned forlate 2015, advances Informatica's metadata-rich capabilities with Live Data Map, to enabledata-driven applications (such as Secure@Souce for tracking and protecting sensitive,private information and Project Sonoma for operationalizing self-service capability).

Alignment with evolving trends and business-facing demand. The linking of Informatica'sdata integration offerings to its self-service data preparation tool facilitates a Microsoft Excel-like interface through which end users can build ETL-type tasks that can be deployed onInformatica Platform. Strong adoption of Informatica's iPaaS aligns well with the growingmovement of data integration architectures toward cloud-based and hybrid delivery models.Informatica's v10 release is expected to feature new capabilities that support any type ofuser, data and mode of deployment.

Cautions

Business evolution. The announced acquisition of Informatica generated some uncertaintyamong prospective and existing customers about the possibility of an impending strategythat could affect Informatica's roadmap and status as a thought-leader. Informatica has toldits customers and partners that its commitment to delivering on its roadmap remainsunchanged.

Cost model. Prospective customers point to difficulty understanding Informatica's licensingand pricing methods. Existing customers often express concerns about high costs relative toalternatives in this market. Informatica has begun to address some of these concerns byintroducing simpler product packaging and pricing, by consolidating multiple add-on products.

Clarity of product messaging and portfolio architecture. Informatica's portfolio has grownlarge, and customers often express confusion about overlapping products and functionality.They want more intuitive ways to understand and navigate the offerings that Informatica'sdata integration tools work with. They also want guidance on how to add new products toexisting Informatica deployments, and easier integrated usage of components.

Information Builders




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Based in New York, New York, U.S., Information Builders offers the following data integrationproducts: iWay Integration Suite (composed of iWay Service Manager and iWay DataMigrator) andiWay Universal Adapter Suite. Information Builders' customer base for this product set isestimated to number more than 800 organizations.

Strengths

Robust functionality and broad usage. Information Builders' data integration tools support adiverse and balanced set of use cases, for which the core functionality remains robust andreliable. The vendor's capabilities in adapters and connectivity, comprehensive datatransformation and encapsulating data into real-time message flows are regarded as keystrengths in deployments.

Synergy of data integration tools with enterprise information capabilities: InformationBuilders continues to focus on evolving an integrated environment for data integrationcapability that can operate with enterprise service bus and master data managementfunctions. This aligns well with demand for support of data integration activities, so thatcompetency teams can seamlessly implement integration, process management, datagovernance and analytics in a synergistic way.

Customer relationship. Reference customers report a positive overall experience withInformation Builders, both before buying and after implementation. Selection of this vendor'sdata integration tools is often influenced by an existing relationship and use of otherInformation Builders products.

Cautions

Mind share with business leaders and influencers. Information Builders appeals mainly totechnical communities and IT buyers, but it has relatively low mind share with businessmanagement and process leaders, who increasingly influence the adoption of informationcapabilities. This creates a market visibility challenge at a time when major competitors areengaging more with those roles.

Adoption scale and learning experience: Implementations of Information Builders' productsby enterprises show an increase in departmental-level and narrower deployments. Manycustomers identify challenges with product complexity, a long learning curve and limitedavailability of skilled practitioners.

Product documentation and time-to-value. Reference customers have stated they want tosee more improvements to Information Builders' documentation of products and bestpractices. Customers seek more extensive documentation of technical components to enableconsistency of developer practices and faster time-to-value in implementations.

MicrosoftBased in Redmond, Washington, U.S., Microsoft offers data integration capabilities via SQL ServerIntegration Services (SSIS), which is included in the SQL Server DBMS license. Vast worldwide

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deployments of Microsoft SQL Server involve usage of SSIS for data integration, althoughMicrosoft does not report a specific customer count for SSIS.

Strengths

Relevant capabilities and TCO. Reference customers cite overall low TCO, speed ofimplementation, ease of use, and the ability to integrate with other Microsoft SQL Servercapabilities as the main reasons for choosing SSIS over alternatives.

Alignment with data management and process- and user-oriented integration: SSISsupports connectivity to diverse data types and broad deployment in Microsoft-centricenvironments. SSIS is often used to put data into SQL Server to enable analytics, datamanagement and end-user data manipulation using Microsoft Office tools, particularly Excel.Using SSIS in conjunction with Microsoft's BizTalk and Azure Data Factory platforms enablesdelivery of data from business workflows in enterprise applications for user-configuredintegration flows.

Widespread tool presence and usage experience. Broad familiarity with the implementationof Microsoft technologies spurs usage of SSIS. Wide choices in terms of communitycollaboration, training, and third-party documentation and guidance for deployment practicesare reported as key points of value.

Cautions

Integration of portfolio. Reference customers cite difficulties with integrated implementationof Microsoft's offerings across its portfolio as they address the growing scale and complexityof deployment scenarios for data integration activities.

Platform support. The inability to deploy data integration workloads on non-Windowsenvironments is a limitation for customers wishing to draw on the processing power ofdiverse hardware and operating system platforms.

Linkage to deployments of information infrastructure. Reference customers cited a desirefor more extensive big data support when manipulating and delivering data of interest, andfor more guidance to enable data quality and governance in relation to data integrationactivities. These challenges relate to the growing complexity of, and demand for, informationcapabilities. Microsoft is progressively enhancing its big data support with links to machinelearning and streaming analytics, and envisaging capabilities for data hub enablement.

OracleBased in Redwood Shores, California, U.S., Oracle offers the following data integration products:Oracle Data Integrator (ODI), Oracle GoldenGate and Oracle Data Service Integrator. Oracle'scustomer base for this product set is estimated to number more than 10,000 organizations.

Strengths

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Broad usage and applicability. Oracle's data integration tool deployments reflect a mix ofuse cases and balanced market traction for ELT capabilities and real-time-oriented CDC andreplication support. Oracle has extended its big data support to enable ingestion ofstreaming data by ODI workflows that can be deployed in Apache Spark and Pigenvironments. To capitalize further on big data and streaming integration scenarios, Oracleis expanding its product development competencies to focus on machine learning in modelingand design processes.

Synergies with portfolio's broad range of technologies. Recognition of Oracle's diverseportfolio for addressing data integration and other data and application-orientedrequirements (spanning data quality tools, MDM solutions, ESB, analytic appliances andenterprise applications) continues to fuel its appeal in deployment scenarios.

Brand awareness and market presence. Oracle's size and global coverage of applicationsand analytics solutions enables it to draw on a huge customer base and a wide productdistribution model for positioning data integration tools. Broad usage of Oracle'stechnologies within its customer base has driven wide availability of community support,training and third-party documentation on implementation practices and approaches toproblem resolution.

Cautions

Functional fulfillment. Although perceptions of Oracle's evolution of its data integrationtools are generally positive, product-related customer satisfaction has declined in relation todevelopers' productivity with newer versions, overall ease of use and time-to-value.Customers want easier deployment of source and target changes, simpler monitoring acrossplatforms, and more control over concurrency and queues.

Customer experience. Customers point to challenges in terms of version upgrades, bugs innew releases, responsiveness and the quality of product support. Customers of Oracle'sdata integration tools identify challenges with the processes for obtaining product support,especially in urgent cases.

Pricing. Concerns about prices, target and source-based licensing requirements, andperceived hardware-oriented cost challenges as deployments broaden have generateddissatisfaction among customers.

SAPBased in Walldorf, Germany, SAP offers the following data integration products: SAP DataServices, SAP Replication Server, SAP Landscape Transformation Replication Server, SAP ProcessOrchestration, SAP Hana Cloud Integration, SAP Hana Enterprise Information Management (EIM,including SAP Hana Smart Data Integration and SAP Hana Smart Data Quality), SAP Agile DataPreparation and SAP PowerDesigner. SAP's customer base for this product set is estimated tonumber more than 15,000 organizations.

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Strengths

Broad usage and functionality. The breadth of functionality available across SAP's portfoliosupports a diverse mix of data integration styles and use cases of increasing complexity.Usage supports synergistic deployments with SAP's broad application and informationinfrastructure offerings. Newly released SAP Hana EIM capabilities in SAP Hana Smart DataIntegration and SAP Hana Smart Data Quality include built-in data integration adapters, aswell a software development kit, which enhances the construction of data access andintegration flows of variable latency involving on-premises and cloud-based data, in-memorydata stores, Apache Spark and NoSQL environments.

Alignment with business-facing demand. Drawing on the linkage of data integration withinformation stewardship, alongside delivery of self-service data preparation functionality,SAP is making collaboration easier between business users and data integrationpractitioners. The launch of SAP Agile Data Preparation, with its user-facing functionality,enables business roles to access data sources, perform data transformations, and modeldatasets of interest in support of business scenarios.

Market presence and links to related disciplines. Capitalizing on its brand recognition,global reach and vast customer base in related disciplines, SAP maintains a high share of themarket's data integration tool adoption. Enterprises with an incumbent portfolio of SAPproducts naturally look to the same vendor to provide their data integration technology.

Cautions

Roadmap alignment and market messaging. There are concerns among customers aboutroadmaps, where the capabilities of SAP's agnostic data integration tools and native Hanaproducts appear to overlap. Concerns about SAP's offerings becoming tightly linked to Hanahave given rise to a perception that SAP is placing less emphasis on addressing the needs ofnon-SAP environments (for timely releases of heterogeneous data connectivity, for example).However, recent product releases and published roadmaps from SAP show continueddevelopment of heterogeneous features in its agnostic data integration tools.

Support for metadata. Although SAP offers extensive metadata and modeling functionalityfor data integration activities through SAP PowerDesigner, some reference customers areunaware of these capabilities and require help to address the growing scale and diversity ofdata integration scenarios that are making metadata management and modeling morecomplex in information infrastructure environments.

Customer support, service experience and skills. Reference customers' feedback indicatesconcerns about the overall customer experience. They want better guidance and support forbest practices to ease the learning curve, wider availability of high-quality professionalservices, and shorter time-to-value for deployments.

SASBased in Cary, North Carolina, U.S., SAS offers the following data integration products: Data

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Management Platform, Federation Server, SAS/Access, SAS Data Loader for Hadoop and SASEvent Stream Processing. SAS's customer base for this product set is estimated to number 14,000organizations.

Strengths

Broad and integrated portfolio. The breadth and completeness of core functions and theintegration of components position SAS to compete with larger and more establishedvendors in the data integration market. SAS's newly introduced Data Loader for Hadoopprovides a guided user interface to facilitate data loading and data preparation (profiling,cleansing and transforming data), one that capitalizes on demand in the market.

Customer relationship. Reference customers report that their relationship with SAS, bothbefore purchasing and after implementation, is exceptional. This contributes to longer-term,recurring engagements.

Product reliability and stability. Reference customers praised SAS's products for stability,reliability, robustness and effectiveness. These qualities, along with synergistic capabilitiesacross portfolio, establish SAS's data integration technology as dependable and mature.

Cautions

Cost and usage. Reference customers expressed concerns about high prices and a licensingmodel that they perceive as limiting their ability to expand deployments. SAS's dataintegration tool exhibits a dominant emphasis on analytics scenarios, which reflects narrowerversatility compared with leading competitors in this market.

Availability of deployment skills. Reference customers expressed a desire for greateravailability of resources who possess a deep knowledge of SAS tools outside its ownprofessional services business, to give them wider procurement and cost options.

Metadata support and ease of deployment. Some reference customers indicaterequirements for more extensive metadata support when using SAS tools for dataintegration. However, recent enhancements provide capabilities that some customers maynot have taken advantage of; these include discovering, integrating and facilitating thereuse of metadata both within and external to SAS technologies. Customers identifydifficulties, and display reduced satisfaction, with tool setup and product version upgradesand migrations.

SyncsortBased in Woodcliff Lake, New Jersey, U.S., Syncsort offers DMX (for Linux, Unix and Windows) andDMX-h (for Hadoop). Syncsort's customer base for this product set is estimated to number 1,500organizations.

Strengths

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Performance of core functionality and time-to-value. Syncsort continues to provide high-performance bulk/batch data movement capabilities with faster time-to-value than manycompetitors. These strengths continue to fulfill requirements for targeted functionality andsuperior performance and throughput.

Capitalization on big data initiatives. Syncsort is widening its data integration focus to workwith diverse parts of the Hadoop ecosystem, interact with streaming data, and supportexternal parallelized processing in offloading heavy legacy-infrastructure-related ETL or ELTworkloads from data warehouses and mainframes to Hadoop. Using its "IntelligentExecution" framework, Syncsort sets out to insulate users from the underlying complexitiesof Hadoop, enable flexible deployment to diverse platforms, and support on-premises orcloud-based deployments.

Customer relationship and track record. Syncsort offers a high quality of service andsupport, and many customers identify its technical support and their overall relationship withSyncsort as positives. With an established track record of optimizing ETL processing, a loyalcustomer base and strategic partners (including Amazon, Cloudera, Cognizant, Dell, Fujitsu,Hortonworks, MapR, Qlik, Splunk, Tableau and Waterline Data), Syncsort has a solidfoundation on which to grow its market presence.

Cautions

Functional coverage and usage. Implementations of Syncsort's capabilities predominantlycenter on bulk/batch data movement, which poses challenges in competitive situations thatrequire a broad range of data integration styles. However, links between Syncsort's toolsand Apache Kafka and Storm are starting to support message-oriented data delivery.

Support for metadata and data quality. While Syncsort is making efforts to extend itsmetadata capabilities, such as by using Apache HCatalog, reference customers cite metadatamanagement as an area requiring improvements in terms of the discovery of metadata inbroad context, ease of access, and reuse in data integration processes. Customers expressa desire for linkages to data quality capabilities in synergy with data integration tool usage.

Availability of skills and evolving cost model. There is a growing desire for greateravailability of resources with a deep knowledge of Syncsort's tools to facilitate wider accessto skills and more cost options. Cost-sensitivity is beginning to surface in broadeningdeployments.

TalendBased in Redwood City, California, U.S., Talend offers Open Studio for Data Integration, EnterpriseData Integration, Platform for Data Services, Platform for Big Data and Integration Cloud. Talend'spaying customer base for this product portfolio is estimated to number more than 3,600organizations.

Strengths

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Portfolio relevance and cost model. Reference customers appreciate the solid performanceof Talend's functionality, its support of diverse use cases, and the lower TCO of Talend'stechnology, relative to competitors. Talend's free open-source offering and affordabledeveloper-based pricing for fully featured software appeal to customers and frequentlyattract usage for augmenting data integration capabilities.

Commitment to big data and evolving trends. Talend continues to benefit from an earlycommitment to big data and Hadoop, with new customer adoption and technologyadvancements such as in-memory processing (with Apache Spark) and the enabling of real-time scenarios. Momentum to support big data, combined with a new iPaaS offering andplans for self-service data preparation capability (using data virtualization and iPaaS) in1Q16, position Talend to expand its market reach.

Adaptable capabilities in a unified product set. Talend's portfolio, including data quality,MDM, business process management, an ESB, and a recently added metadata managementtool, sets out to deepen synergies across information- and application infrastructure-relateduse cases. Customers value the configurability of Talend's tools, which makes them flexibleenough to adapt to the business requirements of data integration processes and theavailability of artifacts built by Talend's practitioner community.

Cautions

Breadth of experience with all data delivery styles and resourcing. While Talend'scapabilities resonate well in bulk/batch-oriented data delivery needs, the company needs toincrease awareness of its support for other data integration styles. Perceived limitations interms of access to skilled resources, integration with incumbent technical environments andstandards, and enterprisewide deployments were expressed by prospective customers.

Implementation guidance and time-to-value. Increased adoption of Talend's offerings isgenerating dissatisfaction with regard to the availability of usage references and best-practice implementation guidance. Deployments exhibit a long time-to-value, compared withmajor alternatives in this market. Customers desire improvements in technical support anddocumentation to ease version upgrades and migrations, tool usage, monitoring andadministration. Talend is making significant investments in this area.

Product and market messaging. Some existing and prospective customers, particularlyorganizations considering putting Talend's portfolio to enterprisewide use, indicate thatTalend does not adequately articulate the more evolved capabilities of its products or theirsynergistic uses.

Vendors Added and DroppedWe review and adjust our inclusion criteria for Magic Quadrants and MarketScopes as marketschange. As a result of these adjustments, the mix of vendors in any Magic Quadrant orMarketScope may change over time. A vendor's appearance in a Magic Quadrant or MarketScopeone year and not the next does not necessarily indicate that we have changed our opinion of that




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vendor. It may be a reflection of a change in the market and, therefore, changed evaluationcriteria, or of a change of focus by that vendor.

AddedDenodo.

DroppedNone, but Cisco (Composite Software) now appears as Cisco.

Inclusion and Exclusion CriteriaTo be included in this Magic Quadrant, vendors must possess within their technology portfolio thesubset of capabilities identified by Gartner as the most critical from within the overall range ofcapabilities expected of data integration tools. Specifically, vendors must deliver the followingfunctional requirements:

Range of connectivity/adapter support (sources and targets) — Native access to relationalDBMS products, plus access to nonrelational legacy data structures, flat files, XML andmessage queues

Mode of connectivity/adapter support (against a range of sources and targets) — Bulk/batchand CDC

Data delivery modes support — At least two modes among bulk/batch data movement,federated/virtualized views, message-oriented delivery, and data replication andsynchronization

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 impactanalysis reporting, ability to synchronize metadata across multiple instances of the tool, andan open metadata repository, including mechanisms for bidirectional sharing of metadatawith other tools

Design and development support — Graphical design/development environment and teamdevelopment capabilities (such as version control and collaboration)

Data governance support — Ability to interoperate at a metadata level with data profilingand/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 marketpenetration and customer base:




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They must generate at least $20 million of their annual software revenue from dataintegration tools, or maintain at least 300 maintenance-paying customers for their dataintegration tools.

They must support data integration tool customers in at least two of the major geographicregions (North America, Latin America, Europe, the Middle East and Africa, and Asia/Pacific).

We excluded vendors that focus on only one specific data subject area (for example, theintegration of customer data), a single industry, or only their own data models and architectures.

There are many vendors of data integration tools that do not meet the above criteria and aretherefore not included in this Magic Quadrant. For example, many vendors provide products toaddress one very specific style of data delivery (such as data federation/virtualization) and cannotsupport other styles. Others provide a range of functionality, but operate only in a specifictechnical environment. Still others operate only in a single region or support only narrow,departmental implementations. Some vendors meet all the functional, deployment and geographicrequirements, but are very new to the data integration tool market and therefore have limitedrevenue and few production customers.

Evaluation CriteriaAbility to ExecuteGartner analysts evaluate technology providers on the quality and efficacy of the processes,systems, methods or procedures that enable IT providers' performance to be competitive, efficientand effective, and to positively affect revenue, retention and reputation. Ultimately, technologyproviders 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 using the followingcriteria:

Product/Service. How well the vendor supports the range of distinguishing data integrationfunctionalities required by the market, the manner (architecture) in which this functionality isdelivered, support for established and emerging deployment models, and the overallusability and consumption of the tools. Product capabilities are critical to the success of dataintegration tool deployments and, therefore, receive a high weighting.

Overall Viability. The magnitude of the vendor's financial resources and the continuity of itspeople and technology, which affect the practical success of the business unit ororganization in generating business results.

Sales Execution/Pricing. The effectiveness of the vendor's pricing model in light of currentcustomer demand trends and spending patterns, and the effectiveness of its direct andindirect sales channels. This criterion is weighted high to reflect the major emphasis of




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buyers on cost models and ROI, and the criticality of consistent sales execution in order todrive a vendor's growth and customer retention.

Market Responsiveness/Record. The degree to which the vendor has demonstrated theability to respond successfully to market demand for data integration capabilities over anextended period, and how well the vendor has acted on the vision of prior years.

Marketing Execution. The overall effectiveness of the vendor's marketing efforts, whichimpacts its mind share, market share and account penetration. The ability of the vendor toadapt to changing demands in the market by aligning its product message with new trendsand end-user interests.

Customer Experience. The level of satisfaction expressed by customers with the vendor'sproduct support and professional services; their overall relationship with the vendor; andtheir perceptions of the value of the vendor's data integration tools relative to costs andexpectations. This criterion retains a weighting of "high" to reflect buyers' scrutiny of theseconsiderations as they seek to derive optimal value from their investments. Analysis andrating of vendors against this criterion are driven directly by the results of a customer surveyexecuted as part of the Magic Quadrant process.

Table 1. Ability to Execute EvaluationCriteria

Evaluation Criteria Weighting

Product/Service High

Overall Viability Medium

Sales Execution/Pricing High

Market Responsiveness/Record Medium

Marketing Execution Medium

Customer Experience High

Operations Not Rated


Completeness of VisionGartner analysts evaluate technology providers on their ability to convincingly articulate logicalstatements about current and future market direction, innovation, customer needs andcompetitive forces, as well as how they map to Gartner's position. Ultimately, technology




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providers are assessed on their understanding of the ways that market forces can be exploited tocreate opportunities.

We assess vendors' Completeness of Vision for the data integration tool market using thefollowing criteria:

Market Understanding. The degree to which the vendor leads the market in recognizingopportunities represented by trends and new directions (technology, product, services orotherwise), and its ability to adapt to significant market inertia and disruption, including thedegree to which the vendor is aligned with the significant trend for synergy with datamanagement and application integration technologies. Given the dynamic nature of thismarket, this item receives a weighting of "high."

Marketing Strategy. The degree to which the vendor's marketing approach aligns withand/or exploits emerging trends and the overall direction of the market.

Sales Strategy. The alignment of the vendor's sales model with the ways in whichcustomers' preferred buying approaches will evolve over time.

Offering (Product) Strategy. The degree to which the vendor's product roadmap reflectsdemand trends in the market, fills current gaps or weaknesses, and includes developmentsthat create competitive differentiation and increased value for customers. In addition, giventhe requirement for data integration tools to support diverse environments for data, deliverymodels, and platform mix, we assess vendors on the degree of openness of their technologyand product strategy. Given the intense evolution of both technology and deploymentmodels in this market, this criterion receives a weighting of "high."

Business Model. The overall approach the vendor takes to execute its strategy for the dataintegration tool market, including diversity of delivery models, packaging and pricing options,and partnership.

Vertical/Industry Strategy. The degree of emphasis the vendor places on vertical solutions,and the vendor's depth of vertical-market expertise.

Innovation. The degree to which the vendor demonstrates creative energy by enhancing itspractices and product capabilities, as well as introducing thought-leading and differentiatingideas and product plans that have the potential to significantly extend or reshape themarket in a way that adds real value for customers. Given the pace of expansion of dataintegration requirements and the highly competitive nature of the market, this criterionreceives a weighting of "high."

Geographic Strategy. The vendor's strategy for expanding its reach into markets beyond itshome region/country, and its approach to achieving a global presence (for example, its directlocal presence and use of resellers and distributors).

Table 2. Completeness of VisionEvaluation Criteria




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Evaluation Criteria Weighting

Market Understanding High

Marketing Strategy Medium

Sales Strategy Medium

Offering (Product) Strategy High

Business Model Medium

Vertical/Industry Strategy Low

Innovation High

Geographic Strategy Medium


Quadrant DescriptionsLeadersLeaders in the data integration tool market are front-runners in the convergence of single-purpose tools into an offering that supports a full range of data delivery styles. They exhibit aclear understanding and vision of where the market is headed, and are strong in establishingdata integration infrastructure as an enterprise standard and as a critical component of moderninformation infrastructure. They support both traditional and new data integration patterns tocapitalize on market demand. Leaders have significant mind share in the market, and resourcesskilled in their tools are readily available. These vendors establish market trends (to a largedegree) by providing new functional capabilities in their products, and by identifying new types ofbusiness problem to which data integration tools can bring significant value. Examples ofdeployments that span multiple projects and types of use case are common among Leaders'customers. Leaders have an established market presence, significant size and a multinationalpresence (directly or through a parent company).

ChallengersChallengers are well-positioned in light of the key trends in the data integration tool market, suchas the need to support multiple styles of data delivery. However, they may not providecomprehensive breadth of functionality, or may be limited to specific technical environments orapplication domains. In addition, their vision may be hampered by a lack of coordinated strategyacross the various products in their data integration tool portfolio. Challengers generally havesubstantial customer bases, an established presence, credibility and viability, althoughimplementations may be of a single-project nature, or reflect multiple projects of a single type (for




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example, predominantly ETL-oriented use cases).

VisionariesVisionaries demonstrate a strong understanding of emerging technology and business trends, ora position well-aligned with current demand, but they lack market awareness or credibility beyondtheir customer base or a single application domain. Visionaries may also fail to provide acomprehensive set of product capabilities. They may be new entrants lacking the installed baseand global presence of larger vendors, although they could also be large, established players inrelated markets that have only recently placed an emphasis on data integration tools. Thegrowing emphasis on aligning data integration tools with the market's demand for interoperabilityof delivery styles, integrated deployment of related offerings (such as data integration and dataquality tools), metadata modeling, support for emerging information and applicationinfrastructures, and deployment models (among other things), is creating challenges for whichvendors must demonstrate vision.

Niche PlayersNiche Players have gaps in both their Completeness of Vision and Ability to Execute. They oftenlack key aspects of product functionality and/or exhibit a narrow focus on their own architecturesand installed bases. Niche Players may have good functional breadth but a limited presence andmind share in this market. With a small customer base and limited resources, they are notrecognized as proven providers of comprehensive data integration tools for enterprise-classdeployments. Many Niche Players have very strong offerings for a specific range of dataintegration problems (for example, a particular set of technical environments or applicationdomains) and deliver substantial value for their customers in the associated segment.

ContextData integration is central to enterprises' information infrastructure. Enterprises pursuingfrictionless sharing of data are increasingly favoring tools that are flexible in regard to time-to-value demands, integration patterns, optimization for cost and delivery models, and synergieswith information and application infrastructures.

Digital business will intensify data integration challenges. Use cases for generating more businessvalue from an enterprise's information will accelerate the need to connect information acrossdistributed data sources in far more diverse ways than has been the case with the traditionalmovement of bulk data. New types of data are emerging with the rise of digital businesses, andintegration leaders now have to factor these into their data integration strategies. Enabling anintegrated, digital business will add further complexity to an organization's data integrationstrategy by requiring a mix of latencies and patterns, as well as hybrid deployments using on-premises and cloud-based models.

Pressures grow in this market as vendors are challenged to address demand trends for




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innovation with the ability to enhance traditional practices and introduce new models andpractices.

Business imperatives to confront new information challenges are driving the need for arealignment of technology vision in this market. Demand trends in 2015 require vendors toincrease their flexibility in approaching comprehensive data integration needs, and todemonstrate a balanced alignment to time-to-value, breadth of data integration functionality,diverse use cases, and quality customer experience. Buyers increasingly favor tool characteristicsthat exhibit end-user relevance, flexibility in cost and delivery models, and synergy withinformation and application infrastructure initiatives.

Market OverviewEnterprises' need to improve the flexibility of their information infrastructure is intensifying theirfocus on data integration activities. More information and application managers are realizing thatdata integration is a critical aspect of their overall enterprise information management (EIM)strategy and information infrastructure. They understand that they need to employ dataintegration capabilities to share data across all organizational and system boundaries.

Gartner estimates that the data integration tool market was worth approximately $2.4 billion inconstant currency at the end of 2014, an increase of 6.9% from 2013. The growth rate is abovethe average for the enterprise software market as a whole, as data integration capabilitycontinues to be considered of critical importance for addressing the diversity of problems andemerging requirements. A projected five-year compound annual growth rate of approximately7.7% will bring the total to more than $3.4 billion by 2019 (see "Forecast: Enterprise SoftwareMarkets, Worldwide, 2012-2019, 2Q15 Update").

Vendors' pursuit of a more comprehensive offering strategy — to support a broad range of usecases and capitalize on new demand — continues to shape this market's competitive landscape.Offerings that help equip enterprises with data integration capability, independent of applications,processes or technology platforms, do well in this market. Competitive pressures are intensifyingthe focus on technologies that support varying styles of data integration beyond bulk/batch,tightened links to data quality tools, and progression toward a model-driven approach that usescommon metadata across the tool portfolio. Evolving their relevance and competitive positioningrequires vendors to extend their vision, deepen their capabilities and broaden the applicability oftheir data integration offerings. This is in line with buyers' expectations for optimal functionality,performance and scalability in data integration tools, to ensure they work well with the samevendor's technology stack and, increasingly, interoperate across related information andapplication infrastructures.

The following trends reflect a shift in demand from buyers, as well as areas of opportunity fortechnology providers to provide thought leadership and innovation to extend this market'sboundaries:




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Growing interest in business moments and recognition of the required speed of digitalbusiness. In the context of digital business, "business moments" — opportunities of shortduration or a point in time that sets in motion a series of events involving people, businessand things — are increasingly attracting the attention of enterprises. They want to harnessdata to seize these moments, which will require data integration support. Data integrationfunctionality provided in a "sandbox" to support analytics is of growing interest; thisapproach enables data to be delivered and manipulated in a physical or virtual manner, foringestion regardless of where it resides; it also encourages experimentation with, and thebuilding of, new models with which to use data of interest. As pressures for real-time dataintegration grow, organizations will need to manage a range of data latencies to make dataavailable for use within acceptable service levels and to match the required speed ofbusiness.

Intensifying pressure for enterprises to modernize and enlarge their data integrationstrategy. Data integration architecture that predominantly uses a single style and form — forexample, batch-oriented, bulk data extract and delivery (accomplished via ETL techniques) —falls short in enterprises that face overwhelming pressure to support real-time operationsand those that require flexible latencies. Data integration tool deployments are emphasizingthe need to support multiple modes of data delivery, including traditional batch/bulk-orienteddata movement, creation of in-memory federated views of data, and low-latency capture andpropagation of events and changed data. Organizations are increasingly driven to positiondata integration as a strategic discipline at the heart of their information infrastructure — toensure it is equipped for comprehensive data capture and delivery, linked to metadatamanagement and data governance support, and applicable to diverse use cases. In addition,implementations need to support multiple types of user experience via tool interfaces thatappeal not only to technical practitioners but also to people in business-facing roles, such asbusiness analysts and end users. Offerings that promote collaboration between businessand IT participants are becoming important as organizations seek adaptive approaches toachieving data integration capabilities.

Requirements to balance cost-effectiveness, incremental functionality, time-to-value andgrowing interest in self-service. Organizations' continued scrutiny of their investments andoptimization of costs is resulting in aggressive behavior on the part of buyers whennegotiating prices with vendors. More organizations are looking for solid basic capabilitiesthat are "good enough," that can be deployed rapidly and that are offered at attractiveprices. Some buyers, furthermore, are taking a targeted approach by acquiring only whatthey need now, while planning for future data integration needs — they don't procure all thecapabilities they want at once. Nor are buyers necessarily looking for a single product or asingle vendor-specific platform to accomplish everything. Vendors have responded to thisdevelopment in various ways, such as by varying their pricing structures and deploymentoptions (open-source, cloud and hybrid models), and extending support for end-userfunctions so that they work with targeted data of interest, especially when requirementsaren't well-defined. Demand from business-facing buyers is also prompting vendors to addfunctionality that supports self-service data integration.




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Expectations for high-quality customer support and services. Faced with a need tooptimize staffing and budgets, as well as mounting pressure for faster and higher-qualitydelivery of solutions, buyers are demanding superior customer service and support fromtechnology providers. In addition to highly responsive and high-quality technical support forproducts, they want direct and frequent interactions with sales teams and executives.Buyers also want wide availability of relevant skills — both within a provider's installed baseand among system integrator partners — and forums where they can share experiences,lessons and solutions with their peers.

Increasing traction of extensive use cases. Usage of data integration tools continues toexpand beyond analytics-related scenarios, as many others are now also driving demand.The need to support operational data consistency, data migration and cloud-relatedintegration is prompting more data integration initiatives than before. The architecturalapproach of the LDW optimizes the repository styles that employ datafederation/virtualization capabilities to enable data services and assimilate data involving avariety of integrated datasets. Big-data-related initiatives require the use of opportunisticanalytics and the exploration of answers to less-well-formed or unexpected businessquestions. The distribution of required computing workloads to parallelized processes inHadoop and alternative NoSQL repositories will continue to advance the ability of dataintegration tools to interact with big data sources and to deliver data to, and executeintegration tasks in, platforms associated with big data environments.

Extension of integration architectures through a combination of cloud and on-premisesdeployments. A hybrid approach to data integration is growing in popularity because itprovides the ability to execute data integration in both cloud and on-premises environments,as appropriate. It enables enterprises to interchange, reuse and deploy artifacts as neededacross both environments. Adoption of this approach is increasing in the wake of the "cloudfirst" focus of some digital business strategies, which emphasizes the use of "lightweight"technologies that are user-oriented and adaptable to change. Customers are looking to gainbusiness agility by, for example, using iPaaS as an extension of their data integrationinfrastructure to manage cloud-related data delivery and address the growing need for datasharing in cloud scenarios.

Need for alignment with application and information infrastructure. More organizationsare selecting data integration tools that provide tight links to data quality tools, to supportcritical information management and governance initiatives. As MDM programs increase innumber and scope, so organizations seek to apply their investments in data integrationtechnology to those initiatives, to enable the movement, transformation and federation ofmaster data. In addition, many organizations are beginning to pursue data integration andapplication integration in a synergistic way, to exploit the intersection of the two disciplines.Aligned application integration and data integration infrastructure, deployed for the fullspectrum of customer-facing interactions and a broad range of operational flows, graduallyoptimizes costs and shared competencies, as compared with the pursuit of disparateapproaches to similar or common use cases (see "Five Reasons to Begin ConvergingApplication and Data Integration"). The expansion of vendors' capabilities into application




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integration provides opportunities to use tools that exploit common areas of bothtechnologies to deliver shared benefits, such as use of CDC tooling that publishes capturedchanges into message queues.

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magic quadrant for data integration tools

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