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DBMS > GridDB vs. Hypertable vs. Kinetica vs. OmniSci

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

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataAn open source BigTable implementation based on distributed file systems such as 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 modelTime Series DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.53
Rank#198  Overall
#10  Time Series DBMS
Score0.53
Rank#199  Overall
#97  Relational DBMS
Score2.08
Rank#105  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
DeveloperToshiba CorporationHypertable Inc.KineticaMapD Technologies, Inc.
Initial release2013200920122016
Current release4.2, June 20190.9.8.11, March 20166.0V4
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C, C++C++ and CUDA
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyesyes
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 indexesyesrestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLSQL92 (advanced edition only), SQL-like TQL (Toshiba Query Language)noSQL-like DML and DDL statementsyes
APIs and other access methodsProprietary protocolC++ API
Thrift
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersyesnoyes 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-slave replicationselectable replication factor on file system levelMaster-slave replicationMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonono
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 controlAccess rights for users can be defined per databasenoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHypertableKineticaOmniSci 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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More resources
GridDBHypertableKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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