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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparisonKinetica  Xexclude from comparisonTimesTen  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 CPUsIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score0.80
Rank#219  Overall
#31  Key-value stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websitefirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
www.kinetica.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationfirebase.google.com/­docs/­firestoredocs.keydb.devdocs.kinetica.comdocs.oracle.com/­database/­timesten-18.1
DeveloperGoogleEQ Alpha Technology Ltd.KineticaOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2017201920121998
Current release7.1, August 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3commercialcommercial
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++
Server operating systemshostedLinuxLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
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.nononono
Secondary indexesyesyes infoby using the Redis Search moduleyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
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
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsLuauser defined functionsPL/SQL
Triggersyes, with Cloud Functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
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 configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesOptimistic locking, atomic execution of commands blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes infoby means of logfiles and checkpoints
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 levelfine grained access rights according to SQL-standard

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More resources
Google Cloud FirestoreKeyDBKineticaTimesTen
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