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DBMS > GridGain vs. Yanza

System Properties Comparison GridGain vs. Yanza

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonYanza  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteTime Series DBMS for IoT Applications
Primary database modelKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#124  Overall
#23  Key-value stores
#62  Relational DBMS
Score0.00
Rank#341  Overall
#31  Time Series DBMS
Websitewww.gridgain.comyanza.com
Technical documentationwww.gridgain.com/­docs/­latest
DeveloperGridGain Systems, Inc.Yanza
Initial release20072015
Current releaseGridGain 8.5.1
License infoCommercial or Open Sourcecommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemsLinux
OS X
Solaris
Windows
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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 indexesyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)no
Triggersyes (cache interceptors and events)yes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)none
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
Foreign keys infoReferential integritynono
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.yes
User concepts infoAccess controlSecurity Hooks for custom implementationsno

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More resources
GridGainYanza
Recent citations in the news

GridGain Announces Keynote Speakers and Pre-Conference Training Day for In-Memory Computing Summit 2020 Virtual Worldwide Conference
15 October 2020, GlobeNewswire

The Past and Future of In-Memory Computing
26 October 2020, Datanami

Global In Memory Data Grid Market (2020 to 2025) - Growth, Trends, and Forecast
28 October 2020, GlobeNewswire

Global In-Memory Data Grid Market 2020 Analysis by Top Key players- Oracle, IBM, Hazelcast, Scale Out Software, Tibco Software, Software AG, Gigaspaces, Gridgain Systems, Alachisoft, Pivotal, Tmaxsoft, Hitachi
29 October 2020, TechnoWeekly

In Memory Computing Market 2020 Insight Analysis, Strategic Assessment, Top Players – Software, Microsoft, GigaSpaces, GridGain Systems, Hazelcast, SAP, Oracle, TIBCO, IBM, Altibase, ScaleOut Software
29 October 2020, TechnoWeekly

provided by Google News

Job opportunities

Senior Consultant - Remote (U.S. and Canada)
GridGain, Foster City, CA

Java Software Engineer
JPMorgan Chase Bank, N.A., Jersey City, NJ

WEBMETHODS PROFESSIONAL SERVICES CONSULTANTS
Software AG Government Solutions, Herndon, VA

Senior Consultant - Remote (U.S. and Canada)
GridGain Systems, Foster City, CA

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