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DBMS > AgensGraph vs. BigObject vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable

System Properties Comparison AgensGraph vs. BigObject vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonBigObject  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAnalytic DBMS for real-time computations and queriesDistributed 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.
Primary database modelGraph DBMS
Relational DBMS
Relational DBMS infoa hierachical model (tree) can be imposedGraph DBMSRelational DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
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
Websitebitnine.net/­agensgraphbigobject.iodgraph.iowww.esgyn.cncloud.google.com/­bigtable
Technical documentationbitnine.net/­documentationdocs.bigobject.iodgraph.io/­docscloud.google.com/­bigtable/­docs
DeveloperBitnine Global Inc.BigObject, Inc.Dgraph Labs, Inc.EsgynGoogle
Initial release20162015201620152015
Current release2.1, December 2018
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree community edition availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoC++, Java
Server operating systemsLinux
OS X
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
Linuxhosted
Data schemedepending on used data modelyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyesno
APIs and other access methodsCypher Query Language
JDBC
fluentd
ODBC
RESTful HTTP API
GraphQL 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)
Supported programming languagesC
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesLuanoJava Stored Proceduresno
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneyesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnono 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)

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More resources
AgensGraphBigObjectDgraphEsgynDBGoogle Cloud Bigtable
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