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DBMS > Dgraph vs. GridDB vs. GridGain vs. Teradata

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

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache IgniteA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsKey-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
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitedgraph.iogriddb.netwww.gridgain.comwww.teradata.com
Technical documentationdgraph.io/­docsdocs.griddb.netwww.gridgain.com/­docs/­index.htmldocs.teradata.com
DeveloperDgraph Labs, Inc.Toshiba CorporationGridGain Systems, Inc.Teradata
Initial release2016201320071984
Current release5.1, August 2022GridGain 8.5.1Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++Java, C++, .Net
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
hosted
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes 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.nonoyesyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLyes infoSQL 2016 + extensions
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)yes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftSource-replica replicationyes (replicated cache)Multi-source replication
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 jobsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesyes
User concepts infoAccess controlno infoPlanned for future releasesAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard
More information provided by the system vendor
DgraphGridDBGridGainTeradata
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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DgraphGridDBGridGainTeradata
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