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DBMS > Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument 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)
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
Score8.05
Rank#50  Overall
#9  Document stores
Score3.71
Rank#83  Overall
#42  Relational DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websitefirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperGoogleMicrosoftSphinx Technologies Inc.
Initial release201720192001
Current releasecloud service with continuous releases3.2.1, January 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes 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.noyes
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.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 proceduresyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Rno
Triggersyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding 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 nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
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.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Azure Active Directory Authenticationno
More information provided by the system vendor
Google Cloud FirestoreMicrosoft Azure Data ExplorerSphinx
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Google Cloud FirestoreMicrosoft Azure Data ExplorerSphinx
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