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DBMS > Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. OrigoDB vs. Stardog

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. OrigoDB vs. Stardog

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonOrigoDB  Xexclude from comparisonStardog  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 platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerA fully ACID in-memory object graph databaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument storeRelational DBMS infocolumn orientedRelational DBMSDocument store
Object oriented DBMS
Graph DBMS
RDF store
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
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitefirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databaseorigodb.comwww.stardog.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlorigodb.com/­docsdocs.stardog.com
DeveloperGoogleMicrosoftMicrosoftRobert Friberg et alStardog-Union
Initial release2017201920102009 infounder the name LiveDB2010
Current releasecloud service with continuous releasesV127.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Sourcecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C#Java
Server operating systemshostedhostedhostedLinux
Windows
Linux
macOS
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyesschema-free and OWL/RDFS-schema support
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-typesyesUser defined using .NET types and collectionsyes
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.noyesyesno infocan be achieved using .NETno infoImport/export of XML data possible
Secondary indexesyesall fields are automatically indexedyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetyesnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
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
ADO.NET
JDBC
ODBC
.NET Client API
HTTP API
LINQ
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, RTransact SQLyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes infoDomain Eventsyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizednone
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.yes, with always 3 replicas availableSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyesdepending on modelyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 Authenticationfine grained access rights according to SQL-standardRole based authorizationAccess rights for users and roles

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More resources
Google Cloud FirestoreMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureOrigoDBStardog
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