GridGain Upgrades Its Live-Action Big Data Processing Platform

 
 
By Chris Preimesberger  |  Posted 2012-03-28
 
 
 

Apache Hadoop, Cassandra and others are getting a lot of attention as batch data analytics tools as enterprises become more aware of them. And they certainly can handle huge amounts of data that are becoming all too common.

But the data on which they operate cannot be in a live production environment; it all has to be completely offline for the analytics applications to work.

Enter newcomer GridGain Systems, which makes a Java-based open-source middleware platform for processing big data workloads in memory and in real time. The Foster City, Calif.-based company on March 26 launched version 4.0 of its homegrown software platform.

Big data doesn't simply indicate volume of data; it also entails velocity and variety of files, logs and machine data, whatever is fed into the batch. GridGain addresses the velocity of big data workloads in addition to volume and variety by processing live data using its own integration of highly scalable compute and in-memory data grid IT.

"Once data is batched, it's dead and there's no way to bring it back to life," Nikita Ivanov, founder and CEO of GridGain Systems, told eWEEK. "If a system isn't processing live data, it isn't delivering big data in real time. There's no point in having the right information too late. Given the global 24-hour work cycle that now exists, companies want and need to be able to take action on data fast."

Ivanov said GridGain 4.0 features the following:

  • Big Data Anywhere capabilities with native lightweight clients for Java, .NET, Python, PHP and C++ as well as native clients for the two largest mobility platforms, iOS and Android.
  • Native language support for Java, Scala and Groovy programming languages.
  • An easy-to-use monitoring and management console for large-scale grid topologies, with both a scriptable command-line-based interface and a GUI-based console.
  • GridGain CloudBoot for efficient deployment and provisioning of GridGain in public cloud deployments, which will ease deployments for cloud service providers such as Rackspace OpenStack, Amazon Elastic Compute Cloud (EC2) and Microsoft Azure.
  • Enterprise-grade security with a comprehensive security model for node discovery and grid clients. The new solution also includes passcode-based security, Java Authentication and Authorization Service-based (JAAS-based) security, as well as secure session support.

GridGain's big data platform is available as free open-source Community Edition and as Enterprise Edition or OEM Edition, both of which include advanced features as well as enterprise-grade support and maintenance.

eWEEK will be examining real-time analytics processing closely in the coming weeks and months.

Chris Preimesberger is eWEEK's Editor for Features and Analysis. Twitter: @editingwhiz

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