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DBMS > GraphDB vs. Linter vs. Microsoft Azure Data Explorer vs. mSQL vs. RDF4J

System Properties Comparison GraphDB vs. Linter vs. Microsoft Azure Data Explorer vs. mSQL vs. RDF4J

Editorial information provided by DB-Engines
NameGraphDB infoformer name: OWLIM  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionEnterprise-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.RDBMS for high security requirementsFully managed big data interactive analytics platformmSQL (Mini SQL) is a simple and lightweight RDBMSRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSRDF store
Secondary database modelsSpatial DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.ontotext.comlinter.ruazure.microsoft.com/­services/­data-explorerhughestech.com.au/­products/­msqlrdf4j.org
Technical documentationgraphdb.ontotext.com/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentation
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperOntotextrelex.ruMicrosoftHughes TechnologiesSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20001990201919942004
Current release10.4, October 2023cloud service with continuous releases4.4, October 2021
License infoCommercial or Open Sourcecommercial infoSome plugins of GraphDB Workbench are open sourcedcommercialcommercialcommercial infofree licenses can be providedOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++CJava
Server operating systemsAll OS with a Java VM
Linux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Unix
Windows
Data schemeschema-free and OWL/RDFS-schema support; RDF shapesyesFixed schema with schema-less datatypes (dynamic)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesno
Secondary indexesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCyesKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersno
APIs and other access methodsGeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Delphi
Java
Perl
PHP
Tcl
Java
PHP
Python
Server-side scripts infoStored procedureswell-defined plugin interfaces; JavaScript server-side extensibilityyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, Rnoyes
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate ConsistencyEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integrityyes infoConstraint checkingyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlDefault 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.fine grained access rights according to SQL-standardAzure Active Directory Authenticationnono
More information provided by the system vendor
GraphDB infoformer name: OWLIMLinterMicrosoft Azure Data ExplorermSQL infoMini SQLRDF4J infoformerly known as Sesame
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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GraphDB infoformer name: OWLIMLinterMicrosoft Azure Data ExplorermSQL infoMini SQLRDF4J infoformerly known as Sesame
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