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DBMS > Kinetica vs. Spark SQL vs. SQream DB vs. TerminusDB

System Properties Comparison Kinetica vs. Spark SQL vs. SQream DB vs. TerminusDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websitewww.kinetica.comspark.apache.org/­sqlsqream.comterminusdb.com
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.comterminusdb.github.io/­terminusdb/­#
DeveloperKineticaApache Software FoundationSQream TechnologiesDataChemist Ltd.
Initial release2012201420172018
Current release7.1, August 20213.5.0 ( 2.13), September 20232022.1.6, December 202211.0.0, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC++, CUDA, Haskell, Java, ScalaProlog, Rust
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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 SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesSQL-like query language (WOQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.Net
JDBC
ODBC
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functionsnouser defined functions in Pythonyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal and vertical partitioningGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneJournaling Streams
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 configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelnoRole-based access control

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More resources
KineticaSpark SQLSQream DBTerminusDB infoformer name was DataChemist
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