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DBMS > Databricks vs. GraphDB vs. Realm vs. Teradata Aster

System Properties Comparison Databricks vs. GraphDB vs. Realm vs. Teradata Aster

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonRealm  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Relational DBMS
Graph DBMS
RDF store
Document storeRelational 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
Score7.41
Rank#52  Overall
#8  Document stores
Websitewww.databricks.comwww.ontotext.comrealm.io
Technical documentationdocs.databricks.comgraphdb.ontotext.com/­documentationrealm.io/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperDatabricksOntotextRealm, acquired by MongoDB in May 2019Teradata
Initial release2013200020142005
Current release10.4, October 2023
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VM
Linux
OS X
Windows
Android
Backend: server-less
iOS
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and OWL/RDFS-schema support; RDF shapesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.yesnonoyes infoin Aster File Store
Secondary indexesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesyes
SQL infoSupport of SQLwith Databricks SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCnoyes
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
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregateswell-defined plugin interfaces; JavaScript server-side extensibilityno inforuns within the applications so server-side scripts are unnecessaryR packages
Triggersnoyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoConstraint checkingnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes infoIn-Memory realmno
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.yesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGraphDB infoformer name: OWLIMRealmTeradata Aster
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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