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DBMS > RDFox vs. SiteWhere vs. Spark SQL vs. STSdb

System Properties Comparison RDFox vs. SiteWhere vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameRDFox  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionHigh performance knowledge graph and semantic reasoning engineM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.oxfordsemantic.techgithub.com/­sitewhere/­sitewherespark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.oxfordsemantic.techsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOxford Semantic TechnologiesSiteWhereApache Software FoundationSTS Soft SC
Initial release2017201020142011
Current release6.0, Septermber 20223.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScalaC#
Server operating systemsLinux
macOS
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Windows
Data schemeyes infoRDF schemaspredefined schemeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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
Secondary indexesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP API
SPARQL 1.1
HTTP RESTJDBC
ODBC
.NET Client API
Supported programming languagesC
Java
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on HBaseyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesreplication via a shared file systemselectable replication factor infobased on HBasenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.yesnono
User concepts infoAccess controlRoles, resources, and access typesUsers with fine-grained authorization conceptnono

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More resources
RDFoxSiteWhereSpark SQLSTSdb
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