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DBMS > Google Cloud Firestore vs. KeyDB vs. Lovefield vs. Sphinx

System Properties Comparison Google Cloud Firestore vs. KeyDB vs. Lovefield vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparisonLovefield  Xexclude from comparisonSphinx  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 protocolsEmbeddable relational database for web apps written in pure JavaScriptOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeKey-value storeRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.63
Rank#54  Overall
#9  Document stores
Score0.63
Rank#232  Overall
#32  Key-value stores
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitefirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
google.github.io/­lovefieldsphinxsearch.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.keydb.devgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsphinxsearch.com/­docs
DeveloperGoogleEQ Alpha Technology Ltd.GoogleSphinx Technologies Inc.
Initial release2017201920142001
Current release2.1.12, February 20173.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScriptC++
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
NetBSD
OS X
Solaris
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 indexesyesno
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 infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query language infovia JavaScript builder patternSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocol
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
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsLuanono
Triggersyes, with Cloud FunctionsnoUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
nonenone
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
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesOptimistic locking, atomic execution of commands blocks and scriptsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDB
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 ACLnono

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More resources
Google Cloud FirestoreKeyDBLovefieldSphinx
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