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DBMS > Citus vs. DataFS vs. Drizzle vs. Splice Machine

System Properties Comparison Citus vs. DataFS vs. Drizzle vs. Splice Machine

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDataFS  Xexclude from comparisonDrizzle  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.citusdata.comnewdatabase.comsplicemachine.com
Technical documentationdocs.citusdata.comdev.mobiland.com/­Overview.xspsplicemachine.com/­how-it-works
DeveloperMobiland AGDrizzle project, originally started by Brian AkerSplice Machine
Initial release2010201820082014
Current release8.1, December 20181.1.263, October 20227.2.4, September 20123.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoGNU GPLOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemsLinuxWindowsFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes
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 functionalityno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyes infowith proprietary extensionsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
Proprietary client DLL
WinRT client
JDBCJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
VB.Net
C
C++
Java
PHP
C#
C++
Java
JavaScript (Node.js)
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.noyes infoJava
Triggersyesno, except callback-events from server when changes happenedno infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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-standardWindows-ProfilePluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standard

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More resources
CitusDataFSDrizzleSplice Machine
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