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

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

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHive  Xexclude from comparisonPrometheus  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 HadoopOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comhive.apache.orgprometheus.iospark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release201220152014
Current release2.0, September 20193.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open 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, JavascriptJavaGoScala
Server operating systemshostedAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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 infoImport of XML data possibleno
Secondary indexestemporal, categoricalyesnono
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/JSON APIJDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and rolesnono

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GeoSpockHivePrometheusSpark SQL
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