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DBMS > Dgraph vs. Fujitsu Enterprise Postgres vs. GridDB vs. Teradata

System Properties Comparison Dgraph vs. Fujitsu Enterprise Postgres vs. GridDB vs. Teradata

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Scalable in-memory time series database optimized for IoT and Big DataA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-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
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitedgraph.iowww.postgresql.fastware.comgriddb.netwww.teradata.com
Technical documentationdgraph.io/­docswww.postgresql.fastware.com/­product-manualsdocs.griddb.netdocs.teradata.com
DeveloperDgraph Labs, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyToshiba CorporationTeradata
Initial release201620131984
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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 languageGoCC++
Server operating systemsLinux
OS X
Windows
Linux
Windows
Linuxhosted
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL 2016 + extensions
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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 proceduresnouser defined functionsnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesyespartitioning by range, list and by hashShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftSource-replica replicationSource-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 systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
DgraphFujitsu Enterprise PostgresGridDBTeradata
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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DgraphFujitsu Enterprise PostgresGridDBTeradata
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