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DBMS > Citus vs. CockroachDB vs. GBase vs. Ignite

System Properties Comparison Citus vs. CockroachDB vs. GBase vs. Ignite

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCockroachDB  Xexclude from comparisonGBase  Xexclude from comparisonIgnite  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.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational 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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitewww.citusdata.comwww.cockroachlabs.comwww.gbase.cnignite.apache.org
Technical documentationdocs.citusdata.comwww.cockroachlabs.com/­docsapacheignite.readme.io/­docs
DeveloperCockroach LabsGeneral Data Technology Co., Ltd.Apache Software Foundation
Initial release2010201520042015
Current release8.1, December 201823.1.1, May 2023GBase 8a, GBase 8s, GBase 8cApache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGoC, Java, PythonC++, Java, .Net
Server operating systemsLinuxLinux
macOS
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 functionalitynoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes, wire compatible with PostgreSQLStandard with numerous extensionsANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCADO.NET
C API
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
C#C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functionsyes (compute grid and cache interceptors can be used instead)
Triggersyesnoyesyes (cache interceptors and events)
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 RAFThorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using RAFTyesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlyesSecurity Hooks for custom implementations

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More resources
CitusCockroachDBGBaseIgnite
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