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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Realm vs. Vitess

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Realm vs. Vitess

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRealm  Xexclude from comparisonVitess  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.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Document storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.60
Rank#52  Overall
#9  Document stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablerealm.iovitess.io
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docsrealm.io/­docsvitess.io/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleRealm, acquired by MongoDB in May 2019The Linux Foundation, PlanetScale
Initial release20162015201520142013
Current release15.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen SourceOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaGo
Server operating systemsLinux
OS X
Windows
LinuxhostedAndroid
Backend: server-less
iOS
Windows
Docker
Linux
macOS
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnonoyes 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
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
MySQL protocol
ODBC
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
.Net
Java infowith Android only
Objective-C
React Native
Swift
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 Proceduresnono inforuns within the applications so server-side scripts are unnecessaryyes infoproprietary syntax
Triggersnononoyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingnoneSharding
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 zonesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes 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 infoIn-Memory realmyes
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)yesUsers with fine-grained authorization concept infono user groups or roles

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DgraphEsgynDBGoogle Cloud BigtableRealmVitess
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