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DBMS > Citus vs. Realm vs. Splice Machine vs. STSdb vs. Teradata Aster

System Properties Comparison Citus vs. Realm vs. Splice Machine vs. STSdb vs. Teradata Aster

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.citusdata.comrealm.iosplicemachine.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.citusdata.comrealm.io/­docssplicemachine.com/­how-it-works
DeveloperRealm, acquired by MongoDB in May 2019Splice MachineSTS Soft SCTeradata
Initial release20102014201420112005
Current release8.1, December 20183.1, March 20214.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, commercial license availablecommercial
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 languageCJavaC#
Server operating systemsLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
WindowsLinux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)yes
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 functionalitynoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyesnoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
.NET Client APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no inforuns within the applications so server-side scripts are unnecessaryyes infoJavanoR packages
Triggersyesyes infoChange Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication
Source-replica replication
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyes infoIn-Memory realmyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
CitusRealmSplice MachineSTSdbTeradata Aster
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