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DBMS > Hive vs. Kinetica vs. OmniSci

System Properties Comparison Hive vs. Kinetica vs. OmniSci

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKinetica  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopGPU-accelerated database for real-time analysis of large and streaming datasetsA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score79.06
Rank#14  Overall
#9  Relational DBMS
Score0.58
Rank#192  Overall
#96  Relational DBMS
Score2.55
Rank#92  Overall
#47  Relational DBMS
Websitehive.apache.orgwww.kinetica.comwww.omnisci.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.kinetica.com/­docswww.omnisci.com/­docs/­latest
DeveloperApache Software Foundation infoinitially developed by FacebookKineticaMapD Technologies, Inc.
Initial release201220122016
Current release2.3.5, May 20196.0V4
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++ and CUDA
Server operating systemsAll OS with a Java VMLinuxLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMaster-slave replicationMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
HiveKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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