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DBMS > 4D vs. Citus vs. Spark SQL vs. STSdb

System Properties Comparison 4D vs. Citus vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonCitus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpark 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 modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.4d.comwww.citusdata.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdeveloper.4d.comdocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncApache Software FoundationSTS Soft SC
Initial release1984201020142011
Current releasev20, April 20238.1, December 20183.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen 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 languageCScalaC#
Server operating systemsOS X
Windows
LinuxLinux
OS X
Windows
Windows
Data schemeyesyesyesyes
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.yesyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92yes infostandard, with numerous extensionsSQL-like DML and DDL statementsno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
.NET Client API
Supported programming languages4D proprietary IDE
PHP
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replication infoother methods possible by using 3rd party extensionsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.nonono
User concepts infoAccess controlUsers and groupsfine grained access rights according to SQL-standardnono

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More resources
4D infoformer name: 4th DimensionCitusSpark SQLSTSdb
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