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DBMS > Citus vs. CockroachDB vs. Infobright vs. Spark SQL vs. Transbase

System Properties Comparison Citus vs. CockroachDB vs. Infobright vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCockroachDB  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendSpark 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 DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.citusdata.comwww.cockroachlabs.comignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.citusdata.comwww.cockroachlabs.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCockroach LabsIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software FoundationTransaction Software GmbH
Initial release20102015200520141987
Current release8.1, December 201823.1.1, May 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0, commercial license availablecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoCScalaC and C++
Server operating systemsLinuxLinux
macOS
Windows
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesdynamic schemayesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 functionalitynononono
Secondary indexesyesyesno infoKnowledge Grid Technology used insteadnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes, wire compatible with PostgreSQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
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.nononoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using RAFTSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnofine grained access rights according to SQL-standard

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More resources
CitusCockroachDBInfobrightSpark SQLTransbase
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