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DBMS > Google Cloud Firestore vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison Google Cloud Firestore vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Solr

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  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.Embeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMSRelational DBMS infocolumn orientedWide column storeSearch 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)
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitefirebase.google.com/­products/­firestoregoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationfirebase.google.com/­docs/­firestoregithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.html
DeveloperGoogleGoogleMicrosoftMicrosoftApache Software Foundation
Initial release20172014201920122006
Current release2.1.12, February 2017cloud service with continuous releases9.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJava
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
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-typesyesyes infosupports customizable data types and automatic typing
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.nonoyesnoyes
Secondary indexesyesyesall fields are automatically indexednoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetnoSolr Parallel SQL Interface
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
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsnoYes, possible languages: KQL, Python, RnoJava plugins
Triggersyes, with Cloud FunctionsUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnooptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnonoyes
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.noAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesyes

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More resources
Google Cloud FirestoreLovefieldMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageSolr
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