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DBMS > GeoSpock vs. HBase vs. Hive vs. PostgreSQL vs. Vitess

System Properties Comparison GeoSpock vs. HBase vs. Hive vs. PostgreSQL vs. Vitess

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonPostgreSQL  Xexclude from comparisonVitess  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 scaleWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitegeospock.comhbase.apache.orghive.apache.orgwww.postgresql.orgvitess.io
Technical documentationhbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.postgresql.org/­docsvitess.io/­docs
DeveloperGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookPostgreSQL Global Development Group infowww.postgresql.org/­developerThe Linux Foundation, PlanetScale
Initial release200820121989 info1989: Postgres, 1996: PostgreSQL2013
Current release2.0, September 20192.3.4, January 20213.1.3, April 202216.3, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoBSDOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaJavaCGo
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VMFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Docker
Linux
macOS
Data schemeyesschema-free, schema definition possibleyesyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexestemporal, categoricalnoyesyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)noSQL-like DML and DDL statementsyes infostandard with numerous extensionsyes infowith proprietary extensions
APIs and other access methodsJDBCJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoproprietary syntax
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
GeoSpockHBaseHivePostgreSQLVitess
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