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DBMS > Dgraph vs. EsgynDB vs. EventStoreDB vs. Google Cloud Bigtable vs. Microsoft Access

System Properties Comparison Dgraph vs. EsgynDB vs. EventStoreDB vs. Google Cloud Bigtable vs. Microsoft Access

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonEventStoreDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelGraph DBMSRelational DBMSEvent StoreKey-value store
Wide column store
Relational 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
Score1.10
Rank#179  Overall
#1  Event Stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitedgraph.iowww.esgyn.cnwww.eventstore.comcloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdgraph.io/­docsdevelopers.eventstore.comcloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperDgraph Labs, Inc.EsgynEvent Store LimitedGoogleMicrosoft
Initial release20162015201220151992
Current release21.2, February 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Sourcecommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
Windows
hostedWindows infoNot a real database server, but making use of DLLs
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesnoyes infobut not compliant to any SQL standard
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
DAO
ODBC
OLE DB
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++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnoJava Stored Proceduresnoyes infosince Access 2010 using the ACE-engine
Triggersnononoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingnone
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 zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
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)
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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)no infoa simple user-level security was built in till version Access 2003

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More resources
DgraphEsgynDBEventStoreDBGoogle Cloud BigtableMicrosoft Access
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