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DBMS > EsgynDB vs. GraphDB vs. HugeGraph vs. Splice Machine

System Properties Comparison EsgynDB vs. GraphDB vs. HugeGraph vs. Splice Machine

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHugeGraph  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.A fast-speed and highly-scalable Graph DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSGraph DBMS
RDF store
Graph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.esgyn.cnwww.ontotext.comgithub.com/­hugegraph
hugegraph.apache.org
splicemachine.com
Technical documentationgraphdb.ontotext.com/­documentationhugegraph.apache.org/­docssplicemachine.com/­how-it-works
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperEsgynOntotextBaiduSplice Machine
Initial release2015200020182014
Current release10.4, October 20230.93.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2.0Open 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 languageC++, JavaJavaJavaJava
Server operating systemsLinuxAll OS with a Java VM
Linux
OS X
Windows
Linux
macOS
Unix
Linux
OS X
Solaris
Windows
Data schemeyesschema-free and OWL/RDFS-schema support; RDF shapesyesyes
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.nonono
Secondary indexesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Groovy
Java
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Procedureswell-defined plugin interfaces; JavaScript server-side extensibilityasynchronous Gremlin script jobsyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnovia hugegraph-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoConstraint checkingyes infoedges in graphyes
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Users, roles and permissionsAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
EsgynDBGraphDB infoformer name: OWLIMHugeGraphSplice Machine
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
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More resources
EsgynDBGraphDB infoformer name: OWLIMHugeGraphSplice Machine
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