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DBMS > GridGain vs. Kinetica

System Properties Comparison GridGain vs. Kinetica

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteGPU-accelerated database for real-time analysis of large and streaming datasets
Primary database modelKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#122  Overall
#21  Key-value stores
#59  Relational DBMS
Score0.57
Rank#198  Overall
#96  Relational DBMS
Websitewww.gridgain.comwww.kinetica.com
Technical documentationwww.gridgain.com/­docs/­latestwww.kinetica.com/­docs
DeveloperGridGain Systems, Inc.Kinetica
Initial release20072012
Current releaseGridGain 8.5.16.0
License infoCommercial or Open Sourcecommercialcommercial
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++, .NetC, C++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Data schemeyesyes
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
Secondary indexesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Master-slave replication
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
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 infoGPU vRAM or System RAM
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users and roles on table level

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More resources
GridGainKinetica
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GridGain's Strong Market Momentum Continued in 2019
16 January 2020, GlobeNewswire

In-Memory Data Grid Market Challenging Health Concerns 2028 – Dagoretti News
23 January 2020, Dagoretti News

GridGain Systems Named to Deloitte 2019 Technology Fast 500™ for Second Consecutive Year
18 November 2019, GlobeNewswire

GridGain Systems Releases GridGain for z/OS, Expanding Its Market-Leading In-Memory Computing Solution to the Mainframe
7 November 2019, GlobeNewswire

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5 June 2019, eWeek

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5 November 2019, Business Wire

The Kinetica Active Analytics Platform and RAPIDS Now Available on Oracle Cloud Infrastructure to Accelerate Predictive Data Analytics Performance
19 November 2019, Yahoo Finance

provided by Google News

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