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DBMS > Apache Hive vs. Databricks

System Properties Comparison Apache Hive vs. Databricks

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonDatabricks  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.
Primary database modelRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score75.77
Rank#16  Overall
#11  Relational DBMS
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Websitehive.apache.orgwww.databricks.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.databricks.com
DeveloperApache Software Foundation infoinitially developed by FacebookDatabricks
Initial release20122013
Current release3.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsAll OS with a Java VMhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes
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.yes
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQL
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregates
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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 roles

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Apache HiveDatabricks
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