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DBMS > Apache Pinot vs. Google Cloud Firestore vs. GridDB vs. GridGain

System Properties Comparison Apache Pinot vs. Google Cloud Firestore vs. GridDB vs. GridGain

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridDB  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Scalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMSDocument storeTime Series DBMSKey-value store
Relational 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
Score7.85
Rank#51  Overall
#8  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitepinot.apache.orgfirebase.google.com/­products/­firestoregriddb.netwww.gridgain.com
Technical documentationdocs.pinot.apache.orgfirebase.google.com/­docs/­firestoredocs.griddb.netwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation and contributorsGoogleToshiba CorporationGridGain Systems, Inc.
Initial release2015201720132007
Current release1.0.0, September 20235.1, August 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen 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 servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++, .Net
Server operating systemsAll OS with a Java JDK11 or higherhostedLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
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.nonoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBCAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesGo
Java
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsnoyes (compute grid and cache interceptors can be used instead)
Triggersyes, with Cloud Functionsyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelACID
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.yesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users can be defined per databaseSecurity Hooks for custom implementations
More information provided by the system vendor
Apache PinotGoogle Cloud FirestoreGridDBGridGain
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
Apache PinotGoogle Cloud FirestoreGridDBGridGain
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