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

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

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionAnalytic 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.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 modelRelational DBMS infoa hierachical model (tree) can be imposedGraph DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitebigobject.iodgraph.iowww.esgyn.cncloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdocs.bigobject.iodgraph.io/­docscloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperBigObject, Inc.Dgraph Labs, Inc.EsgynGoogleMicrosoft
Initial release20152016201520151992
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache 2.0commercialcommercialcommercial 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 infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
LinuxhostedWindows infoNot a real database server, but making use of DLLs
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesnoyes infobut not compliant to any SQL standard
APIs and other access methodsfluentd
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)
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 proceduresLuanoJava Stored Proceduresnoyes infosince Access 2010 using the ACE-engine
Triggersnonononoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesnoneyesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSynchronous 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 methodsnonoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnono
User concepts infoAccess controlnono 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
BigObjectDgraphEsgynDBGoogle Cloud BigtableMicrosoft Access
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