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DBMS > Graph Engine vs. GraphDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Prometheus

System Properties Comparison Graph Engine vs. GraphDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Prometheus

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineEnterprise-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 widely adopted in-memory data gridFully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring system
Primary database modelGraph DBMS
Key-value store
Graph DBMS
RDF store
Key-value storeRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score3.25
Rank#91  Overall
#7  Graph DBMS
#4  RDF stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitewww.graphengine.iowww.ontotext.comhazelcast.comazure.microsoft.com/­services/­data-explorerprometheus.io
Technical documentationwww.graphengine.io/­docs/­manualgraphdb.ontotext.com/­documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperMicrosoftOntotextHazelcastMicrosoft
Initial release20102000200820192015
Current release10.4, October 20235.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
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 language.NET and CJavaJavaGo
Server operating systems.NETAll OS with a Java VM
Linux
OS X
Windows
All OS with a Java VMhostedLinux
Windows
Data schemeyesschema-free and OWL/RDFS-schema support; RDF shapesschema-freeFixed 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-typesNumeric data only
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.nonoyes infothe object must implement a serialization strategyyesno infoImport of XML data possible
Secondary indexesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesall fields are automatically indexedno
SQL infoSupport of SQLnostored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIGeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyeswell-defined plugin interfaces; JavaScript server-side extensibilityyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersnonoyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integritynoyes infoConstraint checkingnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
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.Role-based access controlAzure Active Directory Authenticationno
More information provided by the system vendor
Graph Engine infoformer name: TrinityGraphDB infoformer name: OWLIMHazelcastMicrosoft Azure Data ExplorerPrometheus
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
Graph Engine infoformer name: TrinityGraphDB infoformer name: OWLIMHazelcastMicrosoft Azure Data ExplorerPrometheus
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