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DBMS > Bangdb vs. Dgraph vs. GridDB vs. Teradata

System Properties Comparison Bangdb vs. Dgraph vs. GridDB vs. Teradata

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDgraph  Xexclude from comparisonGridDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDistributed and scalable native Graph DBMSScalable in-memory time series database optimized for IoT and Big DataA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Graph DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitebangdb.comdgraph.iogriddb.netwww.teradata.com
Technical documentationdocs.bangdb.comdgraph.io/­docsdocs.griddb.netdocs.teradata.com
DeveloperSachin Sinha, BangDBDgraph Labs, Inc.Toshiba CorporationTeradata
Initial release2012201620131984
Current releaseBangDB 2.0, October 20215.1, August 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
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, C++GoC++
Server operating systemsLinuxLinux
OS X
Windows
Linuxhosted
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL like support with command line toolnoSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL 2016 + extensions
APIs and other access methodsProprietary protocol
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnononoyes infoUDFs, stored procedures, table functions in parallel
Triggersyes, Notifications (with Streaming only)noyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyesShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Synchronous replication via RaftSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelACID
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 modeyesyes
User concepts infoAccess controlyes (enterprise version only)no infoPlanned for future releasesAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
BangdbDgraphGridDBTeradata
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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BangdbDgraphGridDBTeradata
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