GridGain In-Memory Computing Platform Enjoys Broad Adoption

Sharply rising product downloads, customer success and industry accolades reinforce company strategy to open source its flagship offering

FOSTER CITY, California – July 31, 2014 – Today GridGain™ Systems (, provider of the leading open source In-Memory Computing (IMC) Platform, announced that since its open source announcement on March 3, customer interest in its products has significantly accelerated and product downloads have increased by more than 900 percent in the last four months. For the company, this achievement reinforces the unique advantages of its comprehensive in-memory computing platform, the viability of its open source strategy, and the widespread need of organizations to achieve high-performance, hyperscale computing on commodity hardware.

Mike Matchett, Senior Analyst at the Taneja Group, recently highlighted how GridGain is meeting an urgent market need in his report, Memory is the Hidden Secret to Success with Big Data: "GridGain already provides a robust, proven, scalable, and enterprise-featured in-memory computing platform to serve many types of highly-performant transactional applications. GridGain's Big Data offering positions the company as a potential core data processing platform in the next generation datacenter for all performance-critical applications, whether analytical, transactional or hybrid."

Download the full Taneja Group report at:

Open source strategy and groundbreaking features spur momentum

GridGain attributes this recent momentum to a number of factors, including its decision to make the platform available through an Apache 2.0 license, which delivered the most comprehensive, tested IMC platform universally accessible through open source technology.

"Analytics and Big Data are our bread and butter", said Juho Seppälä, CEO at Intelligentpipe Oy. "GridGain’s In-Memory Computing Platform, with its tremendous open source feature set, has given our developers comprehensive, but ready-made options to organize Big Data very easily. Selecting GridGain over other in-memory offerings in the market has provided our company with an unfair advantage that lets us focus on the core of our Analytics Engine and significantly shorten our solution's time-to-market."

Recently selected by AlwaysOn as a Global 250 winner in recognition of game-changing technology innovation, the company followed up its open source launch with a series of groundbreaking features, including the first true Plug and Play In-Memory Computing Accelerator for Hadoop, and advanced security functionality that enables financial services and other organizations operating in highly regulated industries with high security requirements to pinpoint, track and control exactly who is accessing their data.

"GridGain’s in-memory technology has all the right ingredients to change the face of computing as we know it", said Max Herrmann, Executive Vice President of Marketing at GridGain. "We believe we have taken the necessary steps to deliver in-memory computing in the most universally adoptable way possible. Massive gains in downloads, numerous third party validations, and the success that we’re seeing our customers achieve confirms that we are laying the groundwork for a major shift in computing."

About GridGain™

GridGain develops the leading open source In-Memory Computing Platform, enabling organizations to conquer challenges that traditional technology can’t approach. From high-performance data management and real-time streaming to an industry first in-memory Hadoop accelerator, GridGain provides the most complete end-to-end stack for low-latency, in-memory computing that allows customers to easily innovate ahead of the accelerating pace of business. Fortune 500 companies, top government agencies and innovative mobile and web companies use GridGain to achieve unprecedented computing performance and business insights. GridGain is headquartered in Foster City, California. To download the GridGain In-Memory Computing Platform, please visit


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Michael Burke or Whit Moses
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