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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Teradata Aster vs. Vitess

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Teradata Aster vs. Vitess

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVitess  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.Platform for big data analytics on multistructured data sources and typesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Relational 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
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablevitess.io
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docsvitess.io/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleTeradataThe Linux Foundation, PlanetScale
Initial release20162015201520052013
Current release15.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen 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
LinuxhostedLinuxDocker
Linux
macOS
Data schemeschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
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.nononoyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnoyesyes 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
ODBC
OLE DB
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
C
C#
C++
Java
Python
R
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 ProceduresnoR packagesyes infoproprietary syntax
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingShardingSharding
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 infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes infoSQL Map-Reduce Frameworkno
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 or Eventual Consistency depending on configurationEventual 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 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.nononoyes
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 BigtableTeradata AsterVitess
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