DBMS > Hive
Hive System Properties
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|Editorial information provided by DB-Engines|
|Description||data warehouse software for querying and managing large distributed datasets, built on Hadoop|
|Database model||Relational DBMS|
|Developer||Apache Software Foundation initially developed by Facebook|
|Current release||2.1.1, December 2016|
|License Commercial or Open Source||Open Source Apache Version 2|
|Cloud-based Only available as a cloud service||no|
|Server operating systems||All OS with a Java VM|
|Typing predefined data types such as float or date||yes|
|SQL Support of (almost entire) SQL standard (DML, DDL and DCL statements)||no uses an SQL-like query language (HiveQL)|
|APIs and other access methods||JDBC|
|Supported programming languages||C++|
|Server-side scripts Stored procedures||yes user defined functions and integration of map-reduce|
|Partitioning methods Methods for storing different data on different nodes||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||selectable replication factor|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes query execution via MapReduce|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency|
|Foreign keys Referential integrity||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no|
|Concurrency Support for concurrent manipulation of data||yes|
|Durability Support for making data persistent||yes|
|User concepts Access control||Access rights for users, groups and roles|
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|DB-Engines blog posts|
Why is Hadoop not listed in the DB-Engines Ranking? Big data teams get proactive on data preparation for analytics users IBM Bolsters Spark Ties with Latest SQL Engine DataOps: How To Use Big Data To Achieve A Data-Driven Enterprise Hadoop上で動作するDWH向けプロダクト「Apache Hive 2.3.0」リリース Hortonworks Touts Hive Speedup, ACID to Prevent 'Dirty Reads' provided by Google News Hadoop Developer Data Engineer Data Engineer Data Engineer Hadoop Developer
Big data teams get proactive on data preparation for analytics users
IBM Bolsters Spark Ties with Latest SQL Engine
DataOps: How To Use Big Data To Achieve A Data-Driven Enterprise
Hadoop上で動作するDWH向けプロダクト「Apache Hive 2.3.0」リリース
Hortonworks Touts Hive Speedup, ACID to Prevent 'Dirty Reads'
provided by Google News