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DBMS > Firebase Realtime Database vs. Hypertable vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. Sphinx

System Properties Comparison Firebase Realtime Database vs. Hypertable vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. Sphinx

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHypertable  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.An open source BigTable implementation based on distributed file systems such as HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeWide column storeTime Series DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitefirebase.google.com/­products/­realtime-databasewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­synapse-analyticssphinxsearch.com
Technical documentationfirebase.google.com/­docs/­databasedocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014Hypertable Inc.Circonus LLC.MicrosoftSphinx Technologies Inc.
Initial release20122009201720162001
Current release0.9.8.11, March 2016V0.10.20, January 20183.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++C++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
LinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes infotext, numeric, histogramsyesno
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 indexesyesrestricted infoonly exact value or prefix value scansnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)yesSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
C++ API
Thrift
HTTP APIADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesJava
JavaScript
Objective-C
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored procedureslimited functionality with using 'rules'noyes, in LuaTransact SQLno
TriggersCallbacks are triggered when data changesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelconfigurable replication factor, datacenter awareyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.no
User concepts infoAccess controlyes, based on authentication and database rulesnonoyesno

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More resources
Firebase Realtime DatabaseHypertableIRONdbMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinx
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