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DBMS > Kinetica vs. Quasardb vs. RDF4J vs. Splice Machine

System Properties Comparison Kinetica vs. Quasardb vs. RDF4J vs. Splice Machine

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDistributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRDF storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.kinetica.comquasar.airdf4j.orgsplicemachine.com
Technical documentationdocs.kinetica.comdoc.quasar.ai/­masterrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperKineticaquasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release2012200920042014
Current release7.1, August 20213.14.1, January 20243.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoEclipse Distribution License (EDL), v1.0.Open 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 systemsLinuxBSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesyes
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.nono
Secondary indexesyesyes infowith tagsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyesyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoby using LevelDByes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users and roles on table levelCryptographically strong user authentication and audit trailnoAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaQuasardbRDF4J infoformerly known as SesameSplice Machine
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