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DBMS > Blazegraph vs. GridGain vs. Hive vs. RDFox vs. Spark SQL

System Properties Comparison Blazegraph vs. GridGain vs. Hive vs. RDFox vs. Spark SQL

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonRDFox  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.GridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Relational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteblazegraph.comwww.gridgain.comhive.apache.orgwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationwiki.blazegraph.comwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBlazegraphGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookOxford Semantic TechnologiesApache Software Foundation
Initial release20062007201220172014
Current release2.1.5, March 2019GridGain 8.5.13.1.3, April 20226.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetJavaC++Scala
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
C
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceno
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)selectable replication factorreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyes infoRelationships in Graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Security Hooks for custom implementationsAccess rights for users, groups and rolesRoles, resources, and access typesno

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BlazegraphGridGainHiveRDFoxSpark SQL
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