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DBMS > Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatabase as a Service offering with high compatibility to Microsoft SQL ServerMicrosofts flagship relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score86.18
Rank#16  Overall
#10  Relational DBMS
Score944.96
Rank#3  Overall
#3  Relational DBMS
Score23.72
Rank#35  Overall
#21  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­sql-databasewww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.microsoft.com/­en-US/­sql/­sql-serverspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftMicrosoftApache Software Foundation
Initial release201019892014
Current releaseV12SQL Server 2019, November 20193.3.0, June 2022
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Scala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesyesno
Secondary indexesyesyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languages.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresTransact SQLTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodestables can be distributed across several files (horizontal partitioning); sharding through federationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with always 3 replicas availableyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

More information provided by the system vendor

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

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More resources
Microsoft Azure SQL Database infoformerly SQL AzureMicrosoft SQL ServerSpark SQL
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