Apache Hive
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| Developer(s) | Contributors |
|---|---|
| Stable release |
2.1.1 / December 8, 2016
|
| Development status | Active |
| Written in | Java |
| Operating system | Cross-platform |
| Type | Data warehouse |
| License | Apache License 2.0 |
| Website | hive |
Apache Hive is a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like Queries (HiveQL) into the underlying Java API without the need to implement queries in the low-level Java API. Since most data warehousing applications work with SQL-based querying languages, Hive supports easy portability of SQL-based application to Hadoop. While initially developed by Facebook, Apache Hive is now used and developed by other companies such as Netflix and the Financial Industry Regulatory Authority (FINRA). Amazon maintains a software fork of Apache Hive that is included in Amazon Elastic MapReduce on Amazon Web Services.
Apache Hive supports analysis of large datasets stored in Hadoop's HDFS and compatible file systems such as Amazon S3 filesystem. It provides an SQL-like language called HiveQL with schema on read and transparently converts queries to MapReduce, Apache Tez and Spark jobs. All three execution engines can run in Hadoop YARN. To accelerate queries, it provides indexes, including bitmap indexes. Other features of Hive include:
By default, Hive stores metadata in an embedded Apache Derby database, and other client/server databases like MySQL can optionally be used.
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