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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. PlanetScale

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. PlanetScale

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelGraph DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databaseplanetscale.com
Technical documentationdgraph.io/­docscloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlplanetscale.com/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleMicrosoftPlanetScale
Initial release20162015200820102020
Current releaseV12
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC++Go
Server operating systemsLinux
OS X
Windows
LinuxhostedhostedDocker
Linux
macOS
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yesyes infowith proprietary extensions
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App EngineTransact SQLyes infoproprietary syntax
TriggersnonoCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication using Paxosyes, with always 3 replicas availableMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
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)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
DgraphEsgynDBGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzurePlanetScale
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