Apache Ignite Documentation

GridGain Developer Hub - Apache Ignitetm

Welcome to the Apache Ignite developer hub run by GridGain. Here you'll find comprehensive guides and documentation to help you start working with Apache Ignite as quickly as possible, as well as support if you get stuck.


GridGain also provides Community Edition which is a distribution of Apache Ignite made available by GridGain. It is the fastest and easiest way to get started with Apache Ignite. The Community Edition is generally more stable than the Apache Ignite release available from the Apache Ignite website and may contain extra bug fixes and features that have not made it yet into the release on the Apache website.


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Hadoop Accelerator

In-Memory Plug-n-Play Hadoop Accelerator

Apache Ignite Hadoop Accelerator provides a set of components allowing for in-memory Hadoop job execution and file system operations.


Hadoop Accelerator ships with alternate high-performant implementation of job tracker which replaces standard Hadoop MapReduce. Use it to boost your Hadoop MapReduce job execution performance.

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IGFS - In-Memory FileSystem

Hadoop Accelerator ships with an implementation of Hadoop FileSystem which stores file system data in-memory using distributed Ignite File System (IGFS). Use it to minimize disk IO and improve performance of any file system operations.

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Secondary File System

Hadoop Accelerator ships with an implementation of SecondaryFileSystem. This implementation can be injected into existing IGFS allowing for read-through and write-through behavior over any other Hadoop FileSystem implementation (e.g. HDFS). Use it if you want your IGFS to become an in-memory caching layer over disk-based HDFS or any other Hadoop-compliant file system.

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Supported Hadoop distributions

Apache Ignite Hadoop Accelerator can be used with a number of Hadoop distributions. Each distribution may require specific installation steps.
See the following installation guides for more information:

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Hadoop Accelerator

In-Memory Plug-n-Play Hadoop Accelerator

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