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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure AI Search

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataSearch-as-a-service for web and mobile app development
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#158  Overall
#15  Graph DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablegriddb.netazure.microsoft.com/­en-us/­services/­search
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docsdocs.griddb.netlearn.microsoft.com/­en-us/­azure/­search
DeveloperDgraph Labs, Inc.EsgynGoogleToshiba CorporationMicrosoft
Initial release20162015201520132015
Current release5.1, August 2022V1
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen 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 servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinuxhosted
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyes 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.nonononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresnonono
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesConnector 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseyes infousing Azure authentication
More information provided by the system vendor
DgraphEsgynDBGoogle Cloud BigtableGridDBMicrosoft Azure AI Search
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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More resources
DgraphEsgynDBGoogle Cloud BigtableGridDBMicrosoft Azure AI Search
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