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DBMS > GridGain vs. JaguarDB vs. Microsoft Azure Table Storage

System Properties Comparison GridGain vs. JaguarDB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgnitePerformant, highly scalable DBMS for AI and IoT applicationsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Key-value store
Vector DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.37
Rank#154  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#70  Relational DBMS
Score0.03
Rank#365  Overall
#55  Key-value stores
#17  Vector DBMS
Score3.05
Rank#84  Overall
#6  Wide column stores
Websitewww.gridgain.comwww.jaguardb.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.jaguardb.com/­support.html
DeveloperGridGain Systems, Inc.DataJaguar, Inc.Microsoft
Initial release200720152012
Current releaseGridGain 8.5.13.3 July 2023
License infoCommercial or Open Sourcecommercial, open sourceOpen Source infoGPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLC++ infothe server part. Clients available in other languages
Server operating systemsLinux
OS X
Solaris
Windows
z/OS
Linuxhosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersno
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
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
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 dataACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
rights management via user accountsAccess rights based on private key authentication or shared access signatures

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More resources
GridGainJaguarDBMicrosoft Azure Table Storage
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