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DBMS > Hive vs. Spark SQL

System Properties Comparison Hive vs. Spark SQL

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSpark SQL  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score73.00
Rank#15  Overall
#10  Relational DBMS
Score16.31
Rank#34  Overall
#21  Relational DBMS
Websitehive.apache.orgspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release20122014
Current release2.3.0, July 2017v2.4.0, November 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and rolesno

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More resources
HiveSpark SQL
DB-Engines blog posts

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Conferences and events

Spark + AI Summit
San Francisco, California, 23-25 April 2019

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