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Taneja Blog / Big Data / Data Center Systems

GridGain Turns Over In-Memory Platform To Apache As Ignite Project

Recently I wrapped up a report on GridGain's In Memory Hadoop Accelerator in which I explored how leveraging memory can vastly improve the production performance of many Hadoop MapReduce jobs, and even tackle streaming use cases without re-writing them or implementing newer streaming paradigms. GridGain drops into existing Hadoop environments without much fuss, so it's an easy add-on/upgrade. Now GridGain has just transferred the core in-memory platform over to Apache Software Foundation as the newly accepted Apache incubator Ignite project, completely contributed to the community at large.

Quoting myself from the GridGain blog announcement -

"Clearly the big data ecosystem is evolving, tackling more kinds of analytics and addressing a wider variety of applications, including enterprise operational intelligence (EOI) apps that require faster interactive latencies, predictive machine learning, split-second decision-making, and high-volume processing. In-memory computing is key to profiting from new competitively differentiating big data solutions like these.”

In memory is clearly a big thing. Lots of projects like Impala and Spark are tapping memory as a key resource. We expect to see Apache Ignite compared and contrasted with Spark a lot. Spark was one of the biggest buzzwords heard everywhere at the recent Strata NY show, and promises to simplify dealing with multiple challenging big data complexities including marrying machine learning and stream processing in one platform. But while Spark is a great new paradigm based on in-memory computing, it is essentially a new platform. Ignite will drop in rather seamlessly into existing Hadoop clusters and accelerate MR based applications to the point where it might not be necessary to jump over to Spark just for performance.

We also like the free in-memory upgrade for Hadoop even if you aren't performance challenged and even if you are using Spark for near-real-time use cases, as we'd bet it helps reign in your Hadoop cluster scale-out costs. As it's free and Apache controlled, it seems a no-brainer to add a little Ignite into your big data project plans. GridGain is hoping that Ignite makes it up the Apache food chain soon, and early tabs on downloads seems to show good support for it.

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  • Premiered: 11/06/14
  • Author: Mike Matchett
Topic(s): Big Data In Memory Computing GridGain Apache Ignite

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