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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 IgniteFully vectorized database across both GPUs and CPUs
Primary database modelKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#138  Overall
#26  Key-value stores
#67  Relational DBMS
Score0.74
Rank#202  Overall
#97  Relational DBMS
Websitewww.gridgain.comwww.kinetica.com
Technical documentationwww.gridgain.com/­docs/­latestwww.kinetica.com/­docs
DeveloperGridGain Systems, Inc.Kinetica
Initial release20072012
Current releaseGridGain 8.5.17.1, August 2021
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)Source-replica 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
More information provided by the system vendor
GridGainKinetica
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
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Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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More resources
GridGainKinetica
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