DBMS > Atos Standard Common Repository vs. EDB Postgres vs. Google BigQuery vs. Machbase Neo vs. Microsoft Access

System Properties Comparison Atos Standard Common Repository vs. EDB Postgres vs. Google BigQuery vs. Machbase Neo vs. Microsoft Access

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Large scale data warehouse service with append-only tables

TimeSeries DBMS for AIoT and BigData

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

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.enterprisedb.com

cloud.google.com/bigquery

machbase.com

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

Technical documentation

www.enterprisedb.com/docs

cloud.google.com/bigquery/docs

machbase.com/dbms

developer.microsoft.com/en-us/access

Developer

Atos Convergence Creators

EnterpriseDB

Google

Machbase

Microsoft

Initial release

2016

2005

2010

2013

1992

Current release

1703

14, December 2021

V8.0, August 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

free test version available

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

Java

C++

Server operating systems

Linux

Linux
Windows

hosted

Linux
macOS
Windows

Windows

Not a real database server, but making use of DLLs

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

LDAP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

by hash, list or range

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

volatile and lookup table

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control

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

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