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DBMS > Kinetica vs. Stardog

System Properties Comparison Kinetica vs. Stardog

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionGPU-accelerated database for real-time analysis of large and streaming datasetsSemantic graph DBMS, developed in Java
Primary database modelRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#195  Overall
#97  Relational DBMS
Score0.73
Rank#175  Overall
#13  Graph DBMS
#7  RDF stores
Websitewww.kinetica.comwww.stardog.com
Technical documentationwww.kinetica.com/­docswww.stardog.com/­docs
DeveloperKineticaComplexible Inc.
Initial release20122010
Current release6.04.2.4, March 2017
License infoCommercial or Open Sourcecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java
Server operating systemsLinuxAll OS with a Java VM
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSPARQL is used as query language
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
HTTP API
OWL
SPARQL
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-master replication in HA-Cluster infousing Apache ZooKeeper
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 in HA-Cluster
Foreign keys infoReferential integrityyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users and roles
More information provided by the system vendor
KineticaStardog
Specific characteristicsStardog is a knowledge graph platform backed by a performant, scalable graph database....
» more
Competitive advantagesStardog is uniquely designed to aid in data integration for your complex data. Benefits...
» more
Typical application scenariosStardog is frequently used for: Anti-money laundering & fraud monitoring Customer...
» more
Key customersBosch, Dow Jones, Elsevier, Ericsson, Morgan Stanley, NASA, NIH, Nokia, Salesforce,...
» more
Market metricsStardog's technology is based on ground-breaking research by our founders cited 10,000+...
» more
Licensing and pricing modelsA fully-featured 60-day Trial license is available for those testing Stardog; contact...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
KineticaStardog
Recent citations in the news

Kinetica Brings on Strategic Asia-Pacific Leadership in Response to Strong Market Demand
25 June 2019, Business Wire

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28 June 2019, MarTech Advisor

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provided by Google News




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