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DBMS > Elasticsearch vs. GraphDB vs. Linter vs. Microsoft Azure Data Explorer vs. TigerGraph

System Properties Comparison Elasticsearch vs. GraphDB vs. Linter vs. Microsoft Azure Data Explorer vs. TigerGraph

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-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 platformA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelSearch engineGraph DBMS
RDF store
Relational DBMSRelational DBMS infocolumn orientedGraph DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial 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
Score132.83
Rank#7  Overall
#1  Search engines
Score3.25
Rank#91  Overall
#7  Graph DBMS
#4  RDF stores
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitewww.elastic.co/­elasticsearchwww.ontotext.comlinter.ruazure.microsoft.com/­services/­data-explorerwww.tigergraph.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlgraphdb.ontotext.com/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.tigergraph.com
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperElasticOntotextrelex.ruMicrosoft
Initial release20102000199020192017
Current release8.6, January 202310.4, October 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercial infoSome plugins of GraphDB Workbench are open sourcedcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++C++
Server operating systemsAll OS with a Java VMAll OS with a Java VM
Linux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedLinux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-free and OWL/RDFS-schema support; RDF shapesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyesno
Secondary indexesyes infoAll search fields are automatically indexedyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagestored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCyesKusto Query Language (KQL), SQL subsetSQL-like query language (GSQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
GeoSPARQL
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
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.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++
Java
Server-side scripts infoStored proceduresyeswell-defined plugin interfaces; JavaScript server-side extensibilityyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, Ryes
Triggersyes infoby using the 'percolation' featurenoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoConstraint checkingyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnono
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 AuthenticationRole-based access control
More information provided by the system vendor
ElasticsearchGraphDB infoformer name: OWLIMLinterMicrosoft Azure Data ExplorerTigerGraph
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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