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DBMS > GridGain vs. JaguarDB vs. Quasardb

System Properties Comparison GridGain vs. JaguarDB vs. Quasardb

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonJaguarDB  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgnitePerformant, highly scalable DBMS for AI and IoT applicationsDistributed, high-performance timeseries database
Primary database modelKey-value store
Relational DBMS
Key-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.08
Rank#125  Overall
#25  Key-value stores
#61  Relational DBMS
Score0.04
Rank#339  Overall
#51  Key-value stores
Score0.07
Rank#330  Overall
#29  Time Series DBMS
Websitewww.gridgain.comwww.datajaguar.comquasardb.net
Technical documentationwww.gridgain.com/­docs/­latestwww.datajaguar.com/­support.phpdoc.quasar.ai/­master
DeveloperGridGain Systems, Inc.DataJaguar, Inc.quasardb
Initial release200720152009
Current releaseGridGain 8.5.12.9.4 September 20183.13.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++ infothe server part. Clients available in other languagesC++
Server operating systemsLinux
OS X
Solaris
Windows
LinuxBSD
Linux
OS X
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infointeger and binary
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.yesnono
Secondary indexesyesyesyes infowith tags
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like query language
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
User concepts infoAccess controlSecurity Hooks for custom implementationsrights management via user accountsCryptographically strong user authentication and audit trail

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More resources
GridGainJaguarDBQuasardb
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