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DBMS > RDFox vs. Rockset vs. Splice Machine

System Properties Comparison RDFox vs. Rockset vs. Splice Machine

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Editorial information provided by DB-Engines
NameRDFox  Xexclude from comparisonRockset  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance knowledge graph and semantic reasoning engineA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMS
Secondary database modelsRelational DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score0.82
Rank#212  Overall
#36  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.oxfordsemantic.techrockset.comsplicemachine.com
Technical documentationdocs.oxfordsemantic.techdocs.rockset.comsplicemachine.com/­how-it-works
DeveloperOxford Semantic TechnologiesRocksetSplice Machine
Initial release201720192014
Current release6.0, Septermber 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinux
macOS
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyes infoRDF schemasschema-freeyes
Typing infopredefined data types such as float or dateyesdynamic typingyes
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 infoingestion from XML files supported
Secondary indexesall fields are automatically indexedyes
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsyes
APIs and other access methodsRESTful HTTP API
SPARQL 1.1
HTTP RESTJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
Java
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesreplication via a shared file systemyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlRoles, resources, and access typesAccess rights for users and organizations can be defined via Rockset consoleAccess rights for users, groups and roles according to SQL-standard

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More resources
RDFoxRocksetSplice Machine
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