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GridGain Systems - In-Memory Computing

Personal Information
Organization / Workplace
San Francisco Bay Area, California United States
Occupation
Founder and CTO
Industry
Technology / Software / Internet
Website
About
Developed the technology since 2005, started the company in 2010, and raised $13M total VC to sustain the growth since. In-memory computing is proving to be the most effective, and increasingly the only way, to deliver on the promise of internet scale and big data. That's because in-memory computing uses RAM rather than disk for storage. And RAM is conservatively 5,000 times faster than disk. By moving all of your data from disk into RAM, things get really, really fast. But what if you lose power? Isn't all the data in RAM lost? Not with today's modern in-memory data grid technology. GridGain's solutions are proven across a wide range of mission critical, high availability applications...
Contact Details

Presentations(2)Ìý

Functional Programming in Java - Lessons Learned by GridGain
Functional Programming in Java - Lessons Learned by GridGainFunctional Programming in Java - Lessons Learned by GridGain
Functional Programming in Java - Lessons Learned by GridGain
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Strangeloop2012
Strangeloop2012Strangeloop2012
Strangeloop2012
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Documents(3)Ìý

In-Memory Compute Grids… Explained
In-Memory Compute Grids… ExplainedIn-Memory Compute Grids… Explained
In-Memory Compute Grids… Explained
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In-Memory Data Grids: Explained...
In-Memory Data Grids: Explained...In-Memory Data Grids: Explained...
In-Memory Data Grids: Explained...
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GridGain & Hadoop: Differences & Synergies
GridGain & Hadoop: Differences & SynergiesGridGain & Hadoop: Differences & Synergies
GridGain & Hadoop: Differences & Synergies
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