Data Integration Buyer's Guide

2019 Gartner Critical Capabilities for Data Integration Tools: Key Takeaways

2019 Gartner Critical Capabilities for Data Integration Tools: Key Takeaways

2019 Gartner Critical Capabilities for Data Integration Tools: Key Takeaways

Analyst house Gartner, Inc. has released its 2019 Critical Capabilities for Data Integration Tools, a companion research to the popular Magic Quadrant report. Used in conjunction with the Magic Quadrant, Critical Capabilities is an additional resource which can assist buyers of data and analytics solutions in finding the products that best fit their organizations.

Gartner defines Critical Capabilities as “attributes that differentiate products/services in a class in terms of their quality and performance.” Gartner rates each vendor’s product or service on a five-point (five points being best) scale in terms of how well it delivers each capability. Critical Capabilities shows you which products are best for each use case and includes a comparison graph for each, along with in-depth descriptions on the various points of comparison.

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The study highlights 16 vendors Gartner considers most significant in this software sector and evaluates them against 10 critical capabilities and now six use cases prevalent in the space, including:

  • Optimized analytics
  • Master Data Management
  • Data consistency between operational applications
  • Interenterprise data acquisition
  • Data services orchestration
  • Data migration and consolidation

The editors at Solutions Review have read the report, available here, and pulled out three key takeaways.

Gartner recommends evaluating data integration vendors on metadata support

Each of the 16 providers covered in Gartner’s Critical Capabilities for Data Integration scored adequate or better for bulk/batch data movement support. However, support for other delivery styles is less consistent across the marketplace. Gartner adds: “Metadata support (both passive and active metadata) is now critical as organizations continue to focus on utilizing metadata to optimize (or even automate) integration flows.” Gartner’s evaluation found that products only averaged between 3.6 and 3.7 points for this use case, and, as a result, warrants caution from integration software buyers.

Informatica earns the top spot for each of the 6 use cases

Informatica occupied the top spot spot for each data integration use case, topping out with a score of 4.63 (out of 5) in data migration and consolidation. Reference customers also ranked it in the top-two vendors for its product set in eight out of the 10 critical capabilities. Headlined by strong metadata support, multicloud  integration, and hybrid deployment options, Informatica provides a tool or capability for just about every data management use case. The one thing holding it back, however, is its data virtualization capabilities, which garnered below-average scores relative to the competition.

IBM remains a top choice in data integration software

Informatica may have swept the product and service scores for key integration use cases, but IBM remains a top choice in the market. IBM finished in second-place for each use case, trailing Informatica by a very small total margin. IBM’s strongest scores are seen for data migration and consolidation, data acquisition and sharing, and optimized analytics use cases. IBM’s data integration portfolio is deep and align with its other products, especially machine learning data preparation.

Read Gartner’s Critical Capabilities for Data Integration Tools.

Download Link to Data Integration Vendor Map

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