DBMS > Atos Standard Common Repository vs. Firebird vs. Google BigQuery vs. Microsoft Access vs. mSQL

System Properties Comparison Atos Standard Common Repository vs. Firebird vs. Google BigQuery vs. Microsoft Access vs. mSQL

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

Firebird is an open source RDBMS forked from Borland's InterBase

Large scale data warehouse service with append-only tables

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.)

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Key-value store

Relational DBMS

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

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

www.firebirdsql.org

cloud.google.com/bigquery

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

hughestech.com.au/products/msql

Technical documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

Developer

Atos Convergence Creators

Firebird Foundation

Google

Microsoft

Hughes Technologies

Initial release

2016

2000

As fork of Borland's InterBase

2010

1992

1994

Current release

1703

5.0.0, January 2024

1902 (16.0.11328.20222), March 2019

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

commercial

Bundled with Microsoft Office

commercial

free licenses can be provided

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 and C++

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

LDAP

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

PSQL

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

none

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

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Users with fine-grained authorization concept

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

Google Cloud Identity & Access Management (IAM)

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

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