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DBMS > Databricks vs. GraphDB vs. HugeGraph vs. Microsoft Azure AI Search

System Properties Comparison Databricks vs. GraphDB vs. HugeGraph vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Enterprise-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 DBMSSearch-as-a-service for web and mobile app development
Primary database modelDocument store
Relational DBMS
Graph DBMS
RDF store
Graph DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.25
Rank#91  Overall
#7  Graph DBMS
#4  RDF stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitewww.databricks.comwww.ontotext.comgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.databricks.comgraphdb.ontotext.com/­documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­search
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperDatabricksOntotextBaiduMicrosoft
Initial release2013200020182015
Current release10.4, October 20230.9V1
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedAll OS with a Java VM
Linux
OS X
Windows
Linux
macOS
Unix
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and OWL/RDFS-schema support; RDF shapesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnonono
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 SQLwith Databricks SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
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
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Groovy
Java
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions and aggregateswell-defined plugin interfaces; JavaScript server-side extensibilityasynchronous Gremlin script jobsno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkno
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 integrityyes infoConstraint checkingyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
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.Users, roles and permissionsyes infousing Azure authentication
More information provided by the system vendor
DatabricksGraphDB infoformer name: OWLIMHugeGraphMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Ontotext 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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