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DBMS > Blazegraph vs. Google Cloud Datastore vs. Kinetica vs. RDF4J

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. Kinetica vs. RDF4J

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGPU-accelerated database for real-time analysis of large and streaming datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#188  Overall
#15  Graph DBMS
#8  RDF stores
Score5.51
Rank#67  Overall
#10  Document stores
Score0.80
Rank#190  Overall
#94  Relational DBMS
Score0.58
Rank#222  Overall
#9  RDF stores
Websiteblazegraph.comcloud.google.com/­datastorewww.kinetica.comrdf4j.org
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docswww.kinetica.com/­docsrdf4j.org/­documentation
DeveloperBlazegraphGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2006200820122004
Current release2.1.5, March 20196.0
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++Java
Server operating systemsLinux
OS X
Windows
hostedLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes, details hereyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyesusing Google App Engineuser defined functionsyes
TriggersnoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelno
More information provided by the system vendor
BlazegraphGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesame
News

Blazegraph 2.1.4 Release
29 August 2016

Blazegraph 2.1.2 Release
18 June 2016

Blazegraph 2.1.1 Release!
9 June 2016

Blazegraph 2.1.0 Release!
8 April 2016

Blazegraph 2.0.0 Release!
22 December 2015

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BlazegraphGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesame
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