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DBMS > Citus vs. Kingbase vs. Spark SQL

System Properties Comparison Citus vs. Kingbase vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonKingbase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comwww.kingbase.com.cnspark.apache.org/­sql
Technical documentationdocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBeiJing KINGBASE Information technologies inc.Apache Software Foundation
Initial release201019992014
Current release8.1, December 2018V8.0, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC and JavaScala
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsStandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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CitusKingbaseSpark SQL
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