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DBMS > Apache Pinot vs. GridDB vs. GridGain vs. Quasardb

System Properties Comparison Apache Pinot vs. GridDB vs. GridGain vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonQuasardb  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 DataGridGain is an in-memory computing platform, built on Apache IgniteDistributed, high-performance timeseries database
Primary database modelRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitepinot.apache.orggriddb.netwww.gridgain.comquasar.ai
Technical documentationdocs.pinot.apache.orgdocs.griddb.netwww.gridgain.com/­docs/­index.htmldoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsToshiba CorporationGridGain Systems, Inc.quasardb
Initial release2015201320072009
Current release1.0.0, September 20235.1, August 2022GridGain 8.5.13.14.1, January 2024
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 availablecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, C++, .NetC++
Server operating systemsAll OS with a Java JDK11 or higherLinuxLinux
OS X
Solaris
Windows
BSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infointeger and binary
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.noyesno
Secondary indexesyesyesyes infowith tags
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Supported programming languagesGo
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)with Hadoop integration
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 levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoTransient mode
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsCryptographically strong user authentication and audit trail
More information provided by the system vendor
Apache PinotGridDBGridGainQuasardb
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 PinotGridDBGridGainQuasardb
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