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DBMS > Drizzle vs. GridDB vs. Kinetica vs. OmniSci

System Properties Comparison Drizzle vs. GridDB vs. Kinetica vs. OmniSci

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big DataGPU-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 DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#210  Overall
#10  Time Series DBMS
Score0.56
Rank#199  Overall
#98  Relational DBMS
Score2.74
Rank#103  Overall
#52  Relational DBMS
Websitegriddb.netwww.kinetica.comwww.omnisci.com
Technical documentationgriddb.net/­en/­docs/­documents/­1-1_what-is-griddb.phpwww.kinetica.com/­docswww.omnisci.com/­docs/­latest
DeveloperDrizzle project, originally started by Brian AkerToshiba CorporationKineticaMapD Technologies, Inc.
Initial release2008201320122016
Current release7.2.4, September 20124.2, June 20196.0V4
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C, C++C++ and CUDA
Server operating systemsFreeBSD
Linux
OS X
LinuxLinuxLinux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsSQL92 (advanced edition only), SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsyes
APIs and other access methodsJDBCProprietary protocolRESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.yesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication
Master-slave replication
Master-slave replicationMaster-slave replicationMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseAccess rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
DrizzleGridDBKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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DrizzleGridDBKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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