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DBMS > Apache Spark (SQL) vs. RDFox

System Properties Comparison Apache Spark (SQL) vs. RDFox

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSGraph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score0.24
Rank#299  Overall
#24  Graph DBMS
#12  RDF stores
Websitespark.apache.org/­sqlwww.oxfordsemantic.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oxfordsemantic.tech
DeveloperApache Software FoundationOxford Semantic Technologies
Initial release20142017
Current release3.5.0 ( 2.13), September 20236.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyes 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.no
Secondary indexesno
SQL infoSupport of SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
SPARQL 1.1
Supported programming languagesJava
Python
R
Scala
C
Java
Server-side scripts infoStored proceduresno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonereplication via a shared file system
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoRoles, resources, and access types

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More resources
Apache Spark (SQL)RDFox
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