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DBMS > GeoSpock vs. GridDB vs. HBase vs. Spark SQL vs. STSdb

System Properties Comparison GeoSpock vs. GridDB vs. HBase vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  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 scaleScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMSKey-value store
Secondary database modelsTime Series DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Websitegeospock.comgriddb.nethbase.apache.orgspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationSTS Soft SC
Initial release2013200820142011
Current release2.0, September 20195.1, August 20222.3.4, January 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++JavaScalaC#
Server operating systemshostedLinuxLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Windows
Data schemeyesyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)
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.nononono
Secondary indexestemporal, categoricalyesnonono
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL92, SQL-like TQL (Toshiba Query Language)noSQL-like DML and DDL statementsno
APIs and other access methodsJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
.NET Client API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javanono
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
GeoSpockGridDBHBaseSpark SQLSTSdb
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
GeoSpockGridDBHBaseSpark SQLSTSdb
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