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DBMS > Firebase Realtime Database vs. HarperDB vs. Sphinx vs. Vitess

System Properties Comparison Firebase Realtime Database vs. HarperDB vs. Sphinx vs. Vitess

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHarperDB  Xexclude from comparisonSphinx  Xexclude from comparisonVitess  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Open source search engine for searching in data from different sources, e.g. relational databasesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeDocument storeSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.harperdb.iosphinxsearch.comvitess.io
Technical documentationfirebase.google.com/­docs/­databasedocs.harperdb.io/­docssphinxsearch.com/­docsvitess.io/­docs
DeveloperGoogle infoacquired by Google 2014HarperDBSphinx Technologies Inc.The Linux Foundation, PlanetScale
Initial release2012201720012013
Current release3.1, August 20213.5.1, February 202315.0.2, December 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoGPL version 2, commercial licence availableOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsC++Go
Server operating systemshostedLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnoyes
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 indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like query language (SphinxQL)yes infowith proprietary extensions
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Proprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJava
JavaScript
Objective-C
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
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 procedureslimited functionality with using 'rules'Custom Functions infosince release 3.1noyes infoproprietary syntax
TriggersCallbacks are triggered when data changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definednoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of specific operationsnoACID 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, using LMDByes infoThe original contents of fields are not stored in the Sphinx index.yes
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 rulesAccess rights for users and rolesnoUsers with fine-grained authorization concept infono user groups or roles

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More resources
Firebase Realtime DatabaseHarperDBSphinxVitess
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