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DBMS > FatDB vs. GigaSpaces vs. GridDB vs. JSqlDb

System Properties Comparison FatDB vs. GigaSpaces vs. GridDB vs. JSqlDb

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonJSqlDb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataJavaScript Query Language Database, stores JavaScript objects and primitives
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSDocument store
Object oriented DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitewww.gigaspaces.comgriddb.netjsqldb.org (offline)
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.net
DeveloperFatCloudGigaspaces TechnologiesToshiba CorporationKonrad von Backstrom
Initial release2012200020132018
Current release15.5, September 20205.1, August 20220.8, December 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java, C++, .NetC++
Server operating systemsWindowsLinux
macOS
Solaris
Windows
LinuxLinux
macOS
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.no infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC#.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyes infovia applicationsyesnofunctions in JavaScript
Triggersyes infovia applicationsyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole-based access controlAccess rights for users can be defined per database
More information provided by the system vendor
FatDBGigaSpacesGridDBJSqlDb
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
FatDBGigaSpacesGridDBJSqlDb
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