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DBMS > AllegroGraph vs. Citus vs. Graph Engine

System Properties Comparison AllegroGraph vs. Citus vs. Graph Engine

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonCitus  Xexclude from comparisonGraph Engine infoformer name: Trinity  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 PostgreSQLA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSGraph DBMS
Key-value store
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Websiteallegrograph.comwww.citusdata.comwww.graphengine.io
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.citusdata.comwww.graphengine.io/­docs/­manual
DeveloperFranz Inc.Microsoft
Initial release200420102010
Current release8.0, December 20238.1, December 2018
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL, commercial license also availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC.NET and C
Server operating systemsLinux
OS X
Windows
Linux.NET
Data schemeyes infoRDF schemasyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 functionalityno
Secondary indexesyesyes
SQL infoSupport of SQLSPARQL is used as query languageyes infostandard, with numerous extensionsno
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
F#
Visual Basic
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.yes
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardinghorizontal 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 extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage
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-standard
More information provided by the system vendor
AllegroGraphCitusGraph Engine infoformer name: Trinity
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
News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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More resources
AllegroGraphCitusGraph Engine infoformer name: Trinity
Recent citations in the news

Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?
8 April 2024, TDWI

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18 August 2023, AWS Blog

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10 July 2023, Datanami

Distributed PostgreSQL Benchmarks: Azure Cosmos DB, CockroachDB, and YugabyteDB
8 July 2023, InfoQ.com

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL ...
24 January 2019, Microsoft

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Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

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