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DBMS > Apache Pinot vs. GridDB vs. OpenMLDB vs. RethinkDB

System Properties Comparison Apache Pinot vs. GridDB vs. OpenMLDB vs. RethinkDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGridDB  Xexclude from comparisonOpenMLDB  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyScalable in-memory time series database optimized for IoT and Big DataAn open-source machine learning database that provides a feature platform for training and inferenceDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score2.66
Rank#107  Overall
#20  Document stores
Websitepinot.apache.orggriddb.netopenmldb.airethinkdb.com
Technical documentationdocs.pinot.apache.orgdocs.griddb.netopenmldb.ai/­docs/­zh/­mainrethinkdb.com/­docs
DeveloperApache Software Foundation and contributorsToshiba Corporation4 Paradigm Inc.The Linux Foundation infosince July 2017
Initial release2015201320202009
Current release1.0.0, September 20235.1, August 20222024-2 February 20242.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen SourceOpen 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 languageJavaC++C++, Java, ScalaC++
Server operating systemsAll OS with a Java JDK11 or higherLinuxLinuxLinux
OS X
Windows
Data schemeyesyesFixed schemaschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infostring, binary, float, bool, date, geometry
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
SQLAlchemy
Supported programming languagesGo
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java
Python
Scala
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresnono
TriggersyesnoClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioningSharding inforange based
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 methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC based
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.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardyes infousers and table-level permissions
More information provided by the system vendor
Apache PinotGridDBOpenMLDBRethinkDB
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
Apache PinotGridDBOpenMLDBRethinkDB
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