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

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

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsHigh performance knowledge graph and semantic reasoning engineSpark 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 modelRelational DBMSGraph DBMS
RDF store
Relational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score0.24
Rank#309  Overall
#25  Graph DBMS
#14  RDF stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Websitewww.ibm.com/­products/­netezzawww.oxfordsemantic.techspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMOxford Semantic TechnologiesApache Software FoundationSTS Soft SC
Initial release2000201720142011
Current release6.0, Septermber 20223.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen 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++ScalaC#
Server operating systemsLinux infoincluded in applianceLinux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeyesyes infoRDF schemasyesyes
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.no
Secondary indexesyesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
OLE DB
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
.NET Client API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
Java
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationreplication via a shared file systemnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.yesno
User concepts infoAccess controlUsers with fine-grained authorization conceptRoles, resources, and access typesnono

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More resources
Netezza infoAlso called PureData System for Analytics by IBMRDFoxSpark SQLSTSdb
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