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DBMS > Bangdb vs. GridDB vs. Microsoft Azure Table Storage vs. Netezza

System Properties Comparison Bangdb vs. GridDB vs. Microsoft Azure Table Storage vs. Netezza

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphScalable in-memory time series database optimized for IoT and Big DataA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Time Series DBMSWide column storeRelational DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitebangdb.comgriddb.netazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezza
Technical documentationdocs.bangdb.comdocs.griddb.net
DeveloperSachin Sinha, BangDBToshiba CorporationMicrosoftIBM
Initial release2012201320122000
Current releaseBangDB 2.0, October 20215.1, August 2022
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemsLinuxLinuxhostedLinux infoincluded in appliance
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolSQL92, SQL-like TQL (Toshiba Query Language)noyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnononoyes
Triggersyes, Notifications (with Streaming only)yesnono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container leveloptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesno
User concepts infoAccess controlyes (enterprise version only)Access rights for users can be defined per databaseAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization concept
More information provided by the system vendor
BangdbGridDBMicrosoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBM
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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BangdbGridDBMicrosoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBM
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