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DBMS > ArcadeDB vs. Databricks vs. GraphDB

System Properties Comparison ArcadeDB vs. Databricks vs. GraphDB

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenThe 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.
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Relational DBMS
Graph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#289  Overall
#43  Document stores
#26  Graph DBMS
#42  Key-value stores
#22  Time Series DBMS
Score60.82
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score2.53
Rank#124  Overall
#8  Graph DBMS
#5  RDF stores
Websitearcadedb.comdatabricks.comwww.ontotext.com
Technical documentationdocs.arcadedb.comdatabricks.com/­documentationgraphdb.ontotext.com/­documentation
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperArcade DataDatabricksOntotext
Initial release202120132000
Current releaseSeptember 20219.8, June 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercial infoSome plugins of GraphDB Workbench are open sourced
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VM
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free and OWL/RDFS-schema support; RDF shapes
Typing infopredefined data types such as float or dateyesyes
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.noyesno
Secondary indexesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes
SQL infoSupport of SQLSQL-like query language, no joinswith Databricks SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Supported programming languagesJavaPython
R
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregateswell-defined plugin interfaces; JavaScript server-side extensibility
Triggersno
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)
Foreign keys infoReferential integrityyes inforelationship in graphsyes infoConstraint checking
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
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.
More information provided by the system vendor
ArcadeDBDatabricksGraphDB infoformer name: OWLIM
Specific characteristicsGraphDB Enterprise is a high-performance semantic repository created by Ontotext....
» 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 open data publishing, semantic inferencing...
» more
Key customersBBC, Press Association, Financial Times, DK, Euromoney, The British Museum, Getty...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB-Free is free to use. SE and Enterprise are licensed per CPU-Core used. Perpetual...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
ArcadeDBDatabricksGraphDB infoformer name: OWLIM
Conferences and events

GraphDB 10.1 – An Easy Ride for Beginners & Seasoned Veterans
4pm GMT | 5pm CET, 1 December 2022 (finished)

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