DBMS > DataFS vs. Dolt vs. Google Cloud Datastore vs. Microsoft Access

System Properties Comparison DataFS vs. Dolt vs. Google Cloud Datastore vs. Microsoft Access

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A MySQL compatible DBMS with Git-like versioning of data and schema

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Secondary database models

Graph DBMS

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Website

newdatabase.com

github.com/dolthub/dolt
www.dolthub.com

cloud.google.com/datastore

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

dev.mobiland.com/Overview.xsp

docs.dolthub.com

cloud.google.com/datastore/docs

developer.microsoft.com/en-us/access

Developer

Mobiland AG

DoltHub Inc

Google

Microsoft

Initial release

2018

2008

1992

Current release

1.1.263, October 2022

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Windows

Linux
macOS
Windows

hosted

Windows

Not a real database server, but making use of DLLs

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

CLI Client
HTTP REST

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

.Net
C
C#
C++
VB.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

yes

currently in alpha release

using Google App Engine

yes

since Access 2010 using the ACE-engine

Triggers

no, except callback-events from server when changes happened

yes

Callbacks using the Google Apps Engine

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Windows-Profile

Only one user is configurable, and must be specified in the config file at startup

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

a simple user-level security was built in till version Access 2003

More information provided by the system vendor

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More resources

DB-Engines blog posts

MS Access drops in DB-Engines Ranking
2 May 2013, Paul Andlinger

Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking
3 December 2012, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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