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DBMS > Apache Impala vs. Hive vs. Kinetica vs. Microsoft Azure SQL Database vs. TerarkDB

System Properties Comparison Apache Impala vs. Hive vs. Kinetica vs. Microsoft Azure SQL Database vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAnalytic DBMS for Hadoopdata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteimpala.apache.orghive.apache.orgwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­bytedance/­terarkdb
Technical documentationimpala.apache.org/­impala-docs.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoinitially developed by FacebookKineticaMicrosoftByteDance, originally Terark
Initial release20132012201220102016
Current release4.1.0, June 20223.1.3, April 20227.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2commercialcommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++C++C++
Server operating systemsLinuxAll OS with a Java VMLinuxhosted
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
C++ API
Java API
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infouser defined functions and integration of map-reduceuser defined functionsTransact SQLno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorSource-replica replicationyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaHiveKineticaMicrosoft Azure SQL Database infoformerly SQL AzureTerarkDB
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