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DBMS > gStore vs. Kinetica vs. Spark SQL vs. STSdb

System Properties Comparison gStore vs. Kinetica vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NamegStore  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionA native Graph DBMS to store and maintain very large RDF datasets.Fully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#359  Overall
#37  Graph DBMS
#18  RDF stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteen.gstore.cnwww.kinetica.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationen.gstore.cn/­#/­enDocsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaApache Software FoundationSTS Soft SC
Initial release2016201220142011
Current release1.2, November 20237.1, August 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoBSDcommercialOpen Source infoApache 2.0Open 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++C, C++ScalaC#
Server operating systemsLinuxLinuxLinux
OS X
Windows
Windows
Data schemeschema-free and OWL/RDFS-schema supportyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes 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 indexesyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsHTTP API
SPARQL 1.1
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
Supported programming languagesC++
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonono
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlUsers, roles and permissions, Role-Based Access Control (RBAC) supportedAccess rights for users and roles on table levelnono

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More resources
gStoreKineticaSpark SQLSTSdb
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