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DBMS > Citus vs. Spark SQL vs. Transbase

System Properties Comparison Citus vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionScalable 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 processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#140  Overall
#68  Relational DBMS
Score20.56
Rank#34  Overall
#20  Relational DBMS
Score0.28
Rank#273  Overall
#126  Relational DBMS
Websitewww.citusdata.comspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationdocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperApache Software FoundationTransaction Software GmbH
Initial release201020141987
Current release8.1, December 20183.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCScalaC and C++
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
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 functionalitynono
Secondary indexesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnoneSource-replica replication
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 integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
CitusSpark SQLTransbase
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