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DBMS > AllegroGraph vs. Citus vs. Sphinx vs. Splice Machine

System Properties Comparison AllegroGraph vs. Citus vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonCitus  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteallegrograph.comwww.citusdata.comsphinxsearch.comsplicemachine.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.citusdata.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFranz Inc.Sphinx Technologies Inc.Splice Machine
Initial release2004201020012014
Current release8.0, December 20238.1, December 20183.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL, commercial license also availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Java
Server operating systemsLinux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoRDF schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.no infobulk load of XML files possibleyes infospecific XML type available, but no XML query functionality
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSPARQL is used as query languageyes infostandard, with numerous extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJava
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
AllegroGraphCitusSphinxSplice Machine
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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