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DBMS > Microsoft Azure SQL Database vs. RDF4J vs. Spark SQL

System Properties Comparison Microsoft Azure SQL Database vs. RDF4J vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatabase as a Service offering with high compatibility to Microsoft SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRDF storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­products/­azure-sql/­databaserdf4j.orgspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-us/­azure/­azure-sqlrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release201020042014
Current releaseV123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open 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++JavaScala
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesyes infoRDF Schemasyes
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languages.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresTransact SQLyesno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with always 3 replicas availablenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlfine grained access rights according to SQL-standardnono

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More resources
Microsoft Azure SQL Database infoformerly SQL AzureRDF4J infoformerly known as SesameSpark SQL
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