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DBMS > GridDB vs. HBase vs. Kinetica vs. STSdb

System Properties Comparison GridDB vs. HBase vs. Kinetica vs. STSdb

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelTime Series DBMSWide column storeRelational DBMSKey-value store
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
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitegriddb.nethbase.apache.orgwww.kinetica.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmldocs.kinetica.com
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetKineticaSTS Soft SC
Initial release2013200820122011
Current release5.1, August 20222.3.4, January 20217.1, August 20214.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2commercialOpen Source infoGPLv2, 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++JavaC, C++C#
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
LinuxWindows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)
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 indexesyesnoyesno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
.NET Client API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javauser defined functionsno
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replicationnone
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 Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)nono
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.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table levelno
More information provided by the system vendor
GridDBHBaseKineticaSTSdb
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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GridDBHBaseKineticaSTSdb
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