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DBMS > Firebase Realtime Database vs. Google Cloud Datastore vs. KeyDB vs. Kinetica

System Properties Comparison Firebase Realtime Database vs. Google Cloud Datastore vs. KeyDB vs. Kinetica

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKeyDB  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeDocument storeKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
www.kinetica.com
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsdocs.keydb.devdocs.kinetica.com
DeveloperGoogle infoacquired by Google 2014GoogleEQ Alpha Technology Ltd.Kinetica
Initial release2012200820192012
Current release7.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++
Server operating systemshostedhostedLinuxLinux
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
RESTful HTTP API
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
Server-side scripts infoStored procedureslimited functionality with using 'rules'using Google App EngineLuauser defined functions
TriggersCallbacks are triggered when data changesCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLAccess rights for users and roles on table level

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More resources
Firebase Realtime DatabaseGoogle Cloud DatastoreKeyDBKinetica
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