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DBMS > Google Cloud Firestore vs. KeyDB vs. Kinetica vs. Vitess

System Properties Comparison Google Cloud Firestore vs. KeyDB vs. Kinetica vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparisonKinetica  Xexclude from comparisonVitess  Xexclude from comparison
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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully vectorized database across both GPUs and CPUsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitefirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
www.kinetica.comvitess.io
Technical documentationfirebase.google.com/­docs/­firestoredocs.keydb.devdocs.kinetica.comvitess.io/­docs
DeveloperGoogleEQ Alpha Technology Ltd.KineticaThe Linux Foundation, PlanetScale
Initial release2017201920122013
Current release7.1, August 202115.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++Go
Server operating systemshostedLinuxLinuxDocker
Linux
macOS
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesyes
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 indexesyesyes infoby using the Redis Search moduleyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsLuauser defined functionsyes infoproprietary syntax
Triggersyes, with Cloud Functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesOptimistic locking, atomic execution of commands blocks and scriptsnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
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.simple password-based access control and ACLAccess rights for users and roles on table levelUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud FirestoreKeyDBKineticaVitess
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