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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonLinter  Xexclude from comparisonNSDb  Xexclude from comparisonOpenEdge  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 KubernetesApplication development environment with integrated database management system
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series DBMSRelational DBMS
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
Score3.45
Rank#85  Overall
#46  Relational DBMS
Websitegriddb.netlinter.runsdb.iowww.progress.com/­openedge
Technical documentationdocs.griddb.netnsdb.io/­Architecturedocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperFatCloudToshiba Corporationrelex.ruProgress Software Corporation
Initial release20122013199020171984
Current release5.1, August 2022OpenEdge 12.2, March 2020
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 2.0commercial
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, Scala
Server operating systemsWindowsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes: int, bigint, decimal, stringyes
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.nononoyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query languageyes infoclose to SQL 92
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
JDBC
ODBC
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
Progress proprietary ABL (Advanced Business Language)
Server-side scripts infoStored proceduresyes infovia applicationsnoyes infoproprietary syntax with the possibility to convert from PL/SQLnoyes
Triggersyes infovia applicationsyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardinghorizontal partitioning infosince Version 11.4
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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-standardUsers and groups
More information provided by the system vendor
FatDBGridDBLinterNSDbOpenEdge
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
FatDBGridDBLinterNSDbOpenEdge
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provided by Google News

OpenEdge Application Development | Progress OpenEdge
14 September 2014, Progress Software

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15 April 2024, release.nl

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provided by Google News



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