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DBMS > Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsMicrosofts relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.68
Rank#62  Overall
#5  Wide column stores
Score1078.30
Rank#3  Overall
#3  Relational DBMS
Score17.77
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-ie/­sql/­sql-server/­sql-server-technical-documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftMicrosoftApache Software Foundation
Initial release201219892014
Current releaseSQL Server 2019, November 20192.4.5, February 2020
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

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Implementation languageC++Scala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
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.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languages.Net
C#
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 proceduresnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, 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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDno
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.noyesno
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standardno

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More resources
Microsoft Azure Table StorageMicrosoft SQL ServerSpark SQL
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