Welcome to Apache™ Hadoop®!

The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

The project includes these modules:

Hadoop Common: The common utilities that support the other Hadoop modules.
Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
Hadoop YARN: A framework for job scheduling and cluster resource management.
Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.

Other Hadoop-related projects at Apache include:

Ambari™: A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which includes support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heatmaps and ability to view MapReduce, Pig and Hive applications visually alongwith features to diagnose their performance characteristics in a user-friendly manner.
Avro™: A data serialization system.
Cassandra™: A scalable multi-master database with no single points of failure.
Chukwa™: A data collection system for managing large distributed systems.
HBase™: A scalable, distributed database that supports structured data storage for large tables.
Hive™: A data warehouse infrastructure that provides data summarization and ad hoc querying.
Mahout™: A Scalable machine learning and data mining library.
Pig™: A high-level data-flow language and execution framework for parallel computation.
Spark™: A fast and general compute engine for Hadoop data. Spark provides a simple and expressive programming model that supports a wide range of applications, including ETL, machine learning, stream processing, and graph computation.
Tez™: A generalized data-flow programming framework, built on Hadoop YARN, which provides a powerful and flexible engine to execute an arbitrary DAG of tasks to process data for both batch and interactive use-cases. Tez is being adopted by Hive™, Pig™ and other frameworks in the Hadoop ecosystem, and also by other commercial software (e.g. ETL tools), to replace Hadoop™ MapReduce as the underlying execution engine.
ZooKeeper™: A high-performance coordination service for distributed applications.

To get started, begin here:

Learn about Hadoop by reading the documentation.
Download Hadoop from the release page.
Discuss Hadoop on the mailing list.

Please head to the releases page to download a release of Apache Hadoop.

A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page.

07 July 2017: Release 3.0.0-alpha4 available

This is the fourth alpha release in the 3.0.0 release line. It consists of 814 bug fixes, improvements, and other enhancements since 3.0.0-alpha3. This is planned to be the final alpha release, with the next release being 3.0.0-beta1.

Please note that alpha releases come with no guarantees of quality or API stability, and are not intended for production use.

Users are encouraged to read the overview of major changes coming in 3.0.0. The alpha4 release notes and changelog detail the changes since 3.0.0-alpha3.

08 June, 2017: Release 2.8.1 available

This is a security release in the 2.8.0 release line. It consists of 2.8.0 plus security fixes. Users on 2.8.0 are encouraged to upgrade to 2.8.1.

Please note that 2.8.x release line continues to be not yet ready for production use. Critical issues are being ironed out via testing and downstream adoption. Production users should wait for a subsequent release in the 2.8.x line.

26 May, 2017: Release 3.0.0-alpha3 available

This is a security release in the 3.0.0 release line. It consists of alpha2 plus security fixes, along with necessary build-related fixes. Users on 3.0.0-alpha1 and 3.0.0-alpha2 are encouraged to upgrade to 3.0.0-alpha3.

Please note that alpha releases come with no guarantees of quality or API stability, and are not intended for production use.

Users are encouraged to read the overview of major changes coming in 3.0.0. The alpha3 release notes and changelog detail the changes since 3.0.0-alpha2.

22 March 2017: Release 2.8.0 available

Apache Hadoop 2.8.0 contains a number of significant features and enhancements. For major features and improvements, please refer: overview of major changes coming in 2.8.0. For details of 2917 fixes, improvements, and new features since the previous 2.7.0 release, please check: release notes and changelog

Please note that this release is not yet ready for production use. Critical issues are being ironed out via testing and downstream adoption. Production users should wait for a 2.8.1/2.8.2 release.

25 January, 2017: Release 3.0.0-alpha2 available

This is the second alpha in a series of planned alphas and betas leading up to a 3.0.0 GA release. The intention is to "release early, release often" to quickly iterate on feedback collected from downstream users.

Please note that alpha releases come with no guarantees of quality or API stability, and are not intended for production use.

Users are encouraged to read the overview of major changes coming in 3.0.0. The alpha2 release notes and changelog detail 857 fixes, improvements, and new features since the previous 3.0.0-alpha1 release.

08 October, 2016: Release 2.6.5 available

A point release for the 2.6 line.

Please see the Hadoop 2.6.5 Release Notes for the list of 79 critical bug fixes and since the previous release 2.6.4.

03 September, 2016: Release 3.0.0-alpha1 available

This is the first alpha in a series of planned alphas and betas leading up to a 3.0.0 GA release. The intention is to "release early, release often" to quickly iterate on feedback collected from downstream users.

Please note that alpha releases come with no guarantees of quality or API stability, and are not intended for production use.

Users are encouraged to read the overview of major changes coming in 3.0.0. The full set of release notes and changelog detail all the changes since the previous minor release 2.7.0.

25 August, 2016: Release 2.7.3 available

A point release for the 2.7 line.

Please see the Hadoop 2.7.3 Release Notes for the list of 221 bug fixes and patches since the previous release 2.7.2.

11 February, 2016: Release 2.6.4 available

A point release for the 2.6 line.

Please see the Hadoop 2.6.4 Release Notes for the list of 46 critical bug fixes and since the previous release 2.6.3.

25 January, 2016: Release 2.7.2 (stable) available

A point release for the 2.7 line.

Please see the Hadoop 2.7.2 Release Notes for the list of 155 bug fixes and patches since the previous release 2.7.1.

17 December, 2015: Release 2.6.3 available

A point release for the 2.6 line.

Please see the Hadoop 2.6.3 Release Notes for the list of 35 critical bug fixes and since the previous release 2.6.2.

28 October, 2015: Release 2.6.2 available

A point release for the 2.6 line.

Please see the Hadoop 2.6.2 Release Notes for the list of 15 critical bug fixes and since the previous release 2.6.1.

23 September, 2015: Release 2.6.1 available

A point release for the 2.6 line.

Please see the Hadoop 2.6.1 Release Notes for the list of 158 critical bug fixes and since the previous release 2.6.0.

06 July, 2015: Release 2.7.1 (stable) available

A point release for the 2.7 line. This release is now considered stable.

Please see the Hadoop 2.7.1 Release Notes for the list of 131 bug fixes and patches since the previous release 2.7.0. Please look at the 2.7.0 section below for the list of enhancements enabled by this first stable release of 2.7.x.