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DBMS > Google Cloud Firestore vs. GridDB vs. IRONdb vs. Kinetica

System Properties Comparison Google Cloud Firestore vs. GridDB vs. IRONdb vs. Kinetica

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonGridDB  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionCloud 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 DataA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitefirebase.google.com/­products/­firestoregriddb.netwww.circonus.com/solutions/time-series-database/www.kinetica.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.griddb.netdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.com
DeveloperGoogleToshiba CorporationCirconus LLC.Kinetica
Initial release2017201320172012
Current release5.1, August 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C, C++
Server operating systemshostedLinuxLinuxLinux
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infotext, numeric, histogramsyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsnoyes, in Luauser defined functions
Triggersyes, with Cloud Functionsyesnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationconfigurable replication factor, datacenter awareSource-replica replication
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 jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelnono
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.yesnoyes infoGPU vRAM or System RAM
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 databasenoAccess rights for users and roles on table level
More information provided by the system vendor
Google Cloud FirestoreGridDBIRONdbKinetica
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
Google Cloud FirestoreGridDBIRONdbKinetica
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