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DBMS > Blazegraph vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison Blazegraph vs. Microsoft SQL Server vs. Spark SQL

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Microsofts flagship relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.91
Rank#183  Overall
#16  Graph DBMS
#8  RDF stores
Score970.61
Rank#3  Overall
#3  Relational DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Websiteblazegraph.comwww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationwiki.blazegraph.comdocs.microsoft.com/­en-US/­sql/­sql-serverspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBlazegraphMicrosoftApache Software Foundation
Initial release200619892014
Current release2.1.5, March 2019SQL Server 2019, November 20193.1.1, March 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemsLinux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyes
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 SQLSPARQL is used as query languageyesSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
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 proceduresyesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, 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 Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsyesno
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 controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)fine grained access rights according to SQL-standardno

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