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DBMS > GridDB vs. Kinetica vs. OpenTSDB vs. Splice Machine

System Properties Comparison GridDB vs. Kinetica vs. OpenTSDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonOpenTSDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUsScalable Time Series DBMS based on HBaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.68
Rank#142  Overall
#12  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegriddb.netwww.kinetica.comopentsdb.netsplicemachine.com
Technical documentationdocs.griddb.netdocs.kinetica.comopentsdb.net/­docs/­build/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperToshiba CorporationKineticacurrently maintained by Yahoo and other contributorsSplice Machine
Initial release2013201220112014
Current release5.1, August 20227.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoLGPLOpen Source infoAGPL 3.0, commercial license 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++JavaJava
Server operating systemsLinuxLinuxLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnumeric data for metrics, strings for tagsyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP API
Telnet API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Erlang
Go
Java
Python
R
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoYes, via Full Spark Integration
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 infobased on HBaseImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 RAMnoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
GridDBKineticaOpenTSDBSplice Machine
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
GridDBKineticaOpenTSDBSplice Machine
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