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DBMS > ArcadeDB vs. Databricks vs. RDF4J

System Properties Comparison ArcadeDB vs. Databricks vs. RDF4J

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonDatabricks  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Relational DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitearcadedb.comwww.databricks.comrdf4j.org
Technical documentationdocs.arcadedb.comdocs.databricks.comrdf4j.org/­documentation
DeveloperArcade DataDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release202120132004
Current releaseSeptember 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Unix
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemas
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.noyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language, no joinswith Databricks SQLno
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJavaPython
R
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes
Triggersyes
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlno
More information provided by the system vendor
ArcadeDBDatabricksRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
ArcadeDBDatabricksRDF4J infoformerly known as Sesame
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