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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. PlanetScale

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. PlanetScale

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonPlanetScale  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 fast-speed and highly-scalable Graph DBMSScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Graph DBMSRelational 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
planetscale.com
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docshugegraph.apache.org/­docsplanetscale.com/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleBaiduPlanetScale
Initial release20162015201520182020
Current release0.9
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
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++, JavaJavaGo
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
macOS
Unix
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 indexesyesyesnoyes infoalso supports composite index and range indexyes
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)
Java API
RESTful HTTP API
TinkerPop Gremlin
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
Groovy
Java
Python
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 Proceduresnoasynchronous Gremlin script jobsyes infoproprietary syntax
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
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 zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesvia hugegraph-sparkno
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)Eventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infoedges in graphyes 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 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.nonoyesyes
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)Users, roles and permissionsUsers with fine-grained authorization concept infono user groups or roles

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More resources
DgraphEsgynDBGoogle Cloud BigtableHugeGraphPlanetScale
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