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DBMS > Citus vs. GBase vs. GridDB vs. Hive

System Properties Comparison Citus vs. GBase vs. GridDB vs. Hive

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonHive  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Scalable in-memory time series database optimized for IoT and Big Datadata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitewww.citusdata.comwww.gbase.cngriddb.nethive.apache.org
Technical documentationdocs.citusdata.comdocs.griddb.netcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperGeneral Data Technology Co., Ltd.Toshiba CorporationApache Software Foundation infoinitially developed by Facebook
Initial release2010200420132012
Current release8.1, December 2018GBase 8a, GBase 8s, GBase 8c5.1, August 20223.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, Java, PythonC++Java
Server operating systemsLinuxLinuxLinuxAll OS with a Java VM
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.yes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsnoyes infouser defined functions and integration of map-reduce
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelno
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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users can be defined per databaseAccess rights for users, groups and roles
More information provided by the system vendor
CitusGBaseGridDBHive
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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