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

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

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonLinter  Xexclude from comparisonNSDb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for real-time computations and queriesA .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 Kubernetes
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
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
Websitebigobject.iogriddb.netlinter.runsdb.io
Technical documentationdocs.bigobject.iodocs.griddb.netnsdb.io/­Architecture
DeveloperBigObject, Inc.FatCloudToshiba Corporationrelex.ru
Initial release20152012201319902017
Current release5.1, August 2022
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2.0
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 systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
WindowsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes: int, bigint, decimal, string
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 indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query language
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
.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
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
Server-side scripts infoStored proceduresLuayes infovia applicationsnoyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnoyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
BigObjectFatDBGridDBLinterNSDb
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
BigObjectFatDBGridDBLinterNSDb
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