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DBMS > Apache Spark (SQL) vs. GeoSpock

System Properties Comparison Apache Spark (SQL) vs. GeoSpock

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NameApache Spark (SQL)  Xexclude from comparisonGeoSpock  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingSpatial and temporal data processing engine for extreme data scale
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.80
Rank#31  Overall
#19  Relational DBMS
Websitespark.apache.org/­sqlgeospock.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGeoSpock
Initial release2014
Current release3.5.0 ( 2.13), September 20232.0, September 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaJava, Javascript
Server operating systemsLinux
OS X
Windows
hosted
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesnotemporal, categorical
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for query only (using Presto)
APIs and other access methodsJDBC
ODBC
JDBC
Supported programming languagesJava
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights for users can be defined per table

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More resources
Apache Spark (SQL)GeoSpock
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