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DBMS > Firebase Realtime Database vs. GeoSpock vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Firebase Realtime Database vs. GeoSpock vs. Microsoft Azure Data Explorer vs. Sphinx

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGeoSpock  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be 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.Spatial and temporal data processing engine for extreme data scaleFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSRelational DBMS infocolumn orientedSearch engine
Secondary database modelsTime Series DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitefirebase.google.com/­products/­realtime-databasegeospock.comazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014GeoSpockMicrosoftSphinx Technologies Inc.
Initial release201220192001
Current release2.0, September 2019cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++
Server operating systemshostedhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonoyes
Secondary indexesyestemporal, categoricalall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)Kusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
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, possible languages: KQL, Python, Rno
TriggersCallbacks are triggered when data changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
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
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users can be defined per tableAzure Active Directory Authenticationno

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More resources
Firebase Realtime DatabaseGeoSpockMicrosoft Azure Data ExplorerSphinx
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