In-Memory Computing uses high-performance, integrated, distributed memory systems to compute and transact on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash technologies.
GridGain’s In-Memory Computing Platform is designed to deliver uncompromised performance for a widest set of in-memory computing use cases from high performance computing, to the industry most advanced data grid, to streaming and plug-n-play Hadoop accelerator:
Natively distributed, ACID transactional, MVCC-based, SQL+NoSQL, in-memory object key-value store. The only in-memory data grid proven to scale to billions of transactions per second on commodity hardware.
Massively distributed processing meets Complex Event Processing (CEP) and Streaming Processing with advanced workflow support, windowing, user-defined indexes and more.
Combination of In-Memory File System 100% compatible with Hadoop HDFS and In-Memory MapReduce delivering 100x performance increase. Minimal integration, plug-n-play acceleration with any Hadoop distro.
The easiest way to get started with GridGain in your project is to use Maven dependency management:
<repository>
<id>GridGain External Repository</id>
<url>http://www.gridgainsystems.com:8085/nexus/content/repositories/external</url>
</repository><dependency>
<groupId>org.gridgain</groupId>
<artifactId>gridgain-platform</artifactId>
<version>${gridgain.version}</version>
</dependency>You can copy and paste this snippet into your Maven POM file. Make sure to replace version with the one you need.
Grab the latest binary release and current documentation at www.gridgain.org
Use GitHub issues to file bugs.
GridGain is available under Apache 2.0 license.
Copyright (C) 2007-2014, GridGain Systems, Inc. All Rights Reserved.