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DBMS > AllegroGraph vs. EsgynDB vs. Splice Machine vs. TigerGraph

System Properties Comparison AllegroGraph vs. EsgynDB vs. Splice Machine vs. TigerGraph

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
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
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score1.83
Rank#141  Overall
#13  Graph DBMS
Websiteallegrograph.comwww.esgyn.cnsplicemachine.comwww.tigergraph.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlsplicemachine.com/­how-it-worksdocs.tigergraph.com
DeveloperFranz Inc.EsgynSplice Machine
Initial release2004201520142017
Current release8.0, December 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
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 languageC++, JavaJavaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
Linux
Data schemeyes infoRDF schemasyesyesyes
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.no infobulk load of XML files possiblenono
Secondary indexesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageyesyesSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispJava Stored Proceduresyes infoJavayes
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardRole-based access control
More information provided by the system vendor
AllegroGraphEsgynDBSplice MachineTigerGraph
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

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17 April 2024

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3 April 2024

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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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphEsgynDBSplice MachineTigerGraph
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