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DBMS > Firebase Realtime Database vs. HEAVY.AI vs. Sphinx

System Properties Comparison Firebase Realtime Database vs. HEAVY.AI vs. Sphinx

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSphinx  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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitefirebase.google.com/­products/­realtime-databasegithub.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.com
Technical documentationfirebase.google.com/­docs/­databasedocs.heavy.aisphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014HEAVY.AI, Inc.Sphinx Technologies Inc.
Initial release201220162001
Current release5.10, January 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC++
Server operating systemshostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Proprietary protocol
Supported programming languagesJava
JavaScript
Objective-C
All languages supporting JDBC/ODBC/Thrift
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored procedureslimited functionality with using 'rules'nono
TriggersCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.yes
User concepts infoAccess controlyes, based on authentication and database rulesfine grained access rights according to SQL-standardno

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More resources
Firebase Realtime DatabaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Sphinx
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