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DBMS > GridGain vs. Stardog

System Properties Comparison GridGain vs. Stardog

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteSemantic graph DBMS, developed in Java
Primary database modelKey-value store
Relational DBMS
Graph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.35
Rank#103  Overall
#19  Key-value stores
#52  Relational DBMS
Score0.81
Rank#166  Overall
#12  Graph DBMS
#7  RDF stores
Websitewww.gridgain.comwww.stardog.com
Technical documentationdocs.gridgain.com/­docswww.stardog.com/­docs
DeveloperGridGain Systems, Inc.Complexible Inc.
Initial release20072010
Current releaseGridGain 8.5.14.2.4, 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 languageJava, C++, .NetJava
Server operating systemsLinux
OS X
Solaris
Windows
All 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.yesno infoImport/export of XML data possible
Secondary indexesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSPARQL is used as query language
APIs and other access methodsHDFS API
Hibernate
JCache
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
HTTP API
OWL
SPARQL
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)no
Triggersyes (cache interceptors and events)yes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Master-master replication in HA-Cluster infousing Apache ZooKeeper
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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.yesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users and roles

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More resources
GridGainStardog
Recent citations in the news

Global In-Memory Computing Market Key Players 2019 – IBM, Oracle, QlikTech, SAP, Altibase, GridGain Systems, Microsoft, ScaleOut Software – Industry Reports
22 April 2019, industryreports24.com

GridGain Community Edition Brings Production Readiness to Apache Ignite
5 March 2019, GlobeNewswire

GridGain Unveils Support Offering for Apache Ignite
5 February 2019, GlobeNewswire

GridGain Cloud In-Memory-Computing-Platform-as-a-Service Adds Automatic Data Persistence, High Availability and Immediate Restarts
10 January 2019, GlobeNewswire

GridGain Earns Numerous Prominent Industry Awards in 2018
6 December 2018, GlobeNewswire

provided by Google News

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