Data Management

InterSystems recognized as Strong Performer in Forrester Wave Report

InterSystems debuts in analyst report that cites strengths in performance, data integration, and deployment options

InterSystems, a creative data technology provider dedicated to helping customers solve the most critical scalability, interoperability, and speed problems, was recognized as a Strong Performer in The Forrester Wave ™: Data Management for Analytics, Q1 2023 that ranks top data management and analytics (DMA) vendors.

The Forrester Wave Data Management for Analytics report evaluated DMA vendors based on 26 criteria that include architecture and data modeling capabilities, performance, scale, and use cases.

InterSystems was named as a Strong Performer, and received the highest scores possible in four criteria, which were: product vision, data integration, deployment options, and performance. The report recognizes InterSystems IRIS® data platform for “comprehensive DMA capabilities that are proven at massive scale” and strengths in performance, data integration, and deployment options. The report notes that the company is “a good fit for large companies looking for a high-performance DMA solution across several key use cases that want to extend their architecture toward data fabric.”

“Our debut as a Strong Performer in the Forrester DMA Wave report is, for us, a testament to InterSystems ongoing commitment to delivering high performance data management solutions,” said Scott Gnau, Global Head of Data Platforms at InterSystems. “Business leaders need faster time-to-insight to empower their decision-making, so we focus on making real-time, predictive, and prescriptive insights easy. Our customers’ success is our top priority.”

The next generation InterSystems IRIS data platform combines operational and analytic capabilities with a comprehensive interoperability platform to deliver high performance for real time analytics and mission-critical applications to enable companies extending their architecture toward smart data fabrics.

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