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DBMS > 4D vs. Kinetica vs. Spark SQL vs. SQream DB

System Properties Comparison 4D vs. Kinetica vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemFully 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 workloads
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitewww.4d.comwww.kinetica.comspark.apache.org/­sqlsqream.com
Technical documentationdeveloper.4d.comdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
Developer4D, IncKineticaApache Software FoundationSQream Technologies
Initial release1984201220142017
Current releasev20, April 20237.1, August 20213.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsOS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Types
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.yesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functionsnouser defined functions in Python
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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 and groupsAccess rights for users and roles on table levelno

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More resources
4D infoformer name: 4th DimensionKineticaSpark SQLSQream DB
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