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DBMS > Firebase Realtime Database vs. KeyDB vs. Memcached vs. Splice Machine

System Properties Comparison Firebase Realtime Database vs. KeyDB vs. Memcached vs. Splice Machine

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonKeyDB  Xexclude from comparisonMemcached  Xexclude from comparisonSplice Machine  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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsIn-memory key-value store, originally intended for cachingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasegithub.com/­Snapchat/­KeyDB
keydb.dev
www.memcached.orgsplicemachine.com
Technical documentationfirebase.google.com/­docs/­databasedocs.keydb.devgithub.com/­memcached/­memcached/­wikisplicemachine.com/­how-it-works
DeveloperGoogle infoacquired by Google 2014EQ Alpha Technology Ltd.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSplice Machine
Initial release2012201920032014
Current release1.6.25, March 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoBSD licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
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 indexesnoyes
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.nono
Secondary indexesyesyes infoby using the Redis Search modulenoyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
JavaScript
Objective-C
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
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'Luanoyes infoJava
TriggersCallbacks are triggered when data changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoRepcached, a Memcached patch, provides this functionallityMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integritynononoyes
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, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyes, based on authentication and database rulessimple password-based access control and ACLyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights for users, groups and roles according to SQL-standard

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More resources
Firebase Realtime DatabaseKeyDBMemcachedSplice Machine
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