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DBMS > GeoSpock vs. Hive vs. RDFox vs. Spark SQL

System Properties Comparison GeoSpock vs. Hive vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHive  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaledata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comhive.apache.orgwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockApache Software Foundation infoinitially developed by FacebookOxford Semantic TechnologiesApache Software Foundation
Initial release201220172014
Current release2.0, September 20193.1.3, April 20226.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptJavaC++Scala
Server operating systemshostedAll OS with a Java VMLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexestemporal, categoricalyesno
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Thrift
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
C
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate 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 datanonoACIDno
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.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and rolesRoles, resources, and access typesno

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More resources
GeoSpockHiveRDFoxSpark SQL
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