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DBMS > GraphDB vs. Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer

System Properties Comparison GraphDB vs. Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameGraphDB infoformer name: OWLIM  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparisonJSqlDb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
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.A widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopJavaScript Query Language Database, stores JavaScript objects and primitivesFully managed big data interactive analytics platform
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMSDocument store
Object oriented DBMS
Relational DBMS infocolumn oriented
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
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.ontotext.comhazelcast.comhive.apache.orgjsqldb.org (offline)azure.microsoft.com/­services/­data-explorer
Technical documentationgraphdb.ontotext.com/­documentationhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorer
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperOntotextHazelcastApache Software Foundation infoinitially developed by FacebookKonrad von BackstromMicrosoft
Initial release20002008201220182019
Current release10.4, October 20235.3.6, November 20233.1.3, April 20220.8, December 2018cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VM
Linux
OS X
Windows
All OS with a Java VMAll OS with a Java VMLinux
macOS
Windows
hosted
Data schemeschema-free and OWL/RDFS-schema support; RDF shapesschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyes infothe object must implement a serialization strategynoyes
Secondary indexesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCSQL-like query languageSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subset
APIs and other access methodsGeoSPARQL
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
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored procedureswell-defined plugin interfaces; JavaScript server-side extensibilityyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reducefunctions in JavaScriptYes, possible languages: KQL, Python, R
Triggersnoyes infoEventsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated Mapselectable replication factornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoConstraint checkingnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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 controlAccess rights for users, groups and rolesAzure Active Directory Authentication
More information provided by the system vendor
GraphDB infoformer name: OWLIMHazelcastHiveJSqlDbMicrosoft Azure Data Explorer
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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