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DBMS > Blazegraph vs. Citus vs. Spark SQL

System Properties Comparison Blazegraph vs. Citus vs. Spark SQL

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonCitus  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.Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpark 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteblazegraph.comwww.citusdata.comspark.apache.org/­sql
Technical documentationwiki.blazegraph.comdocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBlazegraphApache Software Foundation
Initial release200620102014
Current release2.1.5, March 20198.1, December 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScala
Server operating systemsLinux
OS X
Windows
LinuxLinux
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.yes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageyes infostandard, with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsnone
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.nono
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)fine grained access rights according to SQL-standardno

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More resources
BlazegraphCitusSpark SQL
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