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DBMS > Greenplum vs. GridDB vs. Kinetica

System Properties Comparison Greenplum vs. GridDB vs. Kinetica

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Scalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitegreenplum.orggriddb.netwww.kinetica.com
Technical documentationdocs.greenplum.orgdocs.griddb.netdocs.kinetica.com
DeveloperPivotal Software Inc.Toshiba CorporationKinetica
Initial release200520132012
Current release7.0.0, September 20235.1, August 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++
Server operating systemsLinuxLinuxLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes 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 infosince Version 4.2nono
Secondary indexesyesyesyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnouser defined functions
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAccess rights for users and roles on table level
More information provided by the system vendor
GreenplumGridDBKinetica
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GreenplumGridDBKinetica
Recent citations in the news

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
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