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DBMS > EXASOL vs. OrigoDB vs. RDFox vs. Spark SQL

System Properties Comparison EXASOL vs. OrigoDB vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonOrigoDB  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A fully ACID in-memory object graph databaseHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Graph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comorigodb.comwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesorigodb.com/­docsdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolRobert Friberg et alOxford Semantic TechnologiesApache Software Foundation
Initial release20002009 infounder the name LiveDB20172014
Current release6.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++Scala
Server operating systemsLinux
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyesyes
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.nono infocan be achieved using .NETno
Secondary indexesyesyesno
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
.NET Client API
HTTP API
LINQ
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.NetC
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesno
Triggersyesyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyesdepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardRole based authorizationRoles, resources, and access typesno

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More resources
EXASOLOrigoDBRDFoxSpark SQL
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