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DBMS > FatDB vs. GridDB vs. Linter vs. NSDb vs. PouchDB

System Properties Comparison FatDB vs. GridDB vs. Linter vs. NSDb vs. PouchDB

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonLinter  Xexclude from comparisonNSDb  Xexclude from comparisonPouchDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable in-memory time series database optimized for IoT and Big DataRDBMS for high security requirementsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitegriddb.netlinter.runsdb.iopouchdb.com
Technical documentationdocs.griddb.netnsdb.io/­Architecturepouchdb.com/­guides
DeveloperFatCloudToshiba Corporationrelex.ruApache Software Foundation
Initial release20122013199020172012
Current release5.1, August 20227.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++C and C++Java, ScalaJavaScript
Server operating systemsWindowsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes: int, bigint, decimal, stringno
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.nononono
Secondary indexesyesyesyesall fields are automatically indexedyes infovia views
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query languageno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
gRPC
HTTP REST
WebSocket
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Java
Scala
JavaScript
Server-side scripts infoStored proceduresyes infovia applicationsnoyes infoproprietary syntax with the possibility to convert from PL/SQLnoView functions in JavaScript
Triggersyes infovia applicationsyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoby using IndexedDB, WebSQL or LevelDB as backend
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 applicationsAccess rights for users can be defined per databasefine grained access rights according to SQL-standardno
More information provided by the system vendor
FatDBGridDBLinterNSDbPouchDB
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
FatDBGridDBLinterNSDbPouchDB
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