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June 7, 2016

Cray Named Strong Performer in Big Data Hadoop Optimized Systems by Forrester Research

SEATTLE, Wash., June 7 — Global supercomputer leader Cray Inc. (Nasdaq: CRAY) today announced that Forrester Research has named Cray a “strong performer” in The Forrester Wave: Big Data Hadoop Optimized Systems, Q2 2016 report. The independent research firm used a 26-point criteria evaluation system that covered current offering, strategy, and market presence in the evaluation of seven leading vendors in the report.

Authored by Forrester Research analysts Mike Gualtieri and Noel Yuhanna, the Wave report states: “Cray brings its high-performance computing experience to Hadoop. When it comes to supercomputers, Cray is a brand that has been around for more than 40 years, and this tradition and experience is now making its way into big data architectures. Cray offers strong capabilities for interconnected, memory-centric architectures, and its optimized performance lets it handle various workloads… Cray includes fast interconnects and an on-node dense memory hierarchy architecture that positions its analytics platform well for supporting new and emerging in-memory workloads, such as graph analytics, machine learning, and IoT. Cray’s strong high- performance computing history, good technical support, and continued focus and commitment to analytics and big data will appeal to a larger audience in the coming years.”

The Wave report also states: “General-purpose hardware infrastructure requires considerable time and effort to install, configure, tune, upgrade, and monitor Hadoop platforms,” according to the authors of the report. “Hadoop-optimized systems help overcome these issues by optimizing the infrastructure with automation, balanced system resources, and integrated testing… This market is growing because enterprise architecture pros see Hadoop-optimized systems as a strategic platform to support their big data initiatives. When selecting a system, enterprises should look at modularity, automation, performance, and overall price/performance attributes.”

“We are excited by this ranking of strong performer in The Forrester Wave: Big Data Hadoop Optimized Systems report,” said Ryan Waite, Cray’s senior vice president of products. “We believe this recognition of the Urika system reinforces our leadership position in providing customers with a powerful tool for solving the most advanced analytics challenges. And on the heels of unveiling our new agile analytics platform, the Cray Urika-GX system, our offering proves to be even stronger. By fusing supercomputing technologies with an open, enterprise-ready software framework for big data analytics, our Urika-GX system gives customers unprecedented versatility for running multiple analytics workloads concurrently on a single platform that leverages the speed of a Cray supercomputer.”

Upcoming Cray Webinar: Why Big Data Analytics Needs to Be Agile Now

Reserve your spot for Wednesday, June 8, at 9:00 a.m. PDT and join Cray’s senior vice president of products, Ryan Waite, and featured guest Mike Gualtieri, Forrester Research principal analyst, for a discussion on how analytics is becoming more dynamic.

For more information on the Cray Urika-GX system, please visit the Cray website at

About Cray Inc.

Global supercomputing leader Cray Inc. (Nasdaq: CRAY) provides innovative systems and solutions enabling scientists and engineers in industry, academia and government to meet existing and future simulation and analytics challenges. Leveraging more than 40 years of experience in developing and servicing the world’s most advanced supercomputers, Cray offers a comprehensive portfolio of supercomputers and big data storage and analytics solutions delivering unrivaled performance, efficiency and scalability. Cray’s Adaptive Supercomputing vision is focused on delivering innovative next-generation products that integrate diverse processing technologies into a unified architecture, allowing customers to meet the market’s continued demand for realized performance. Go to for more information.

Source: Cray