DBMS > Atos Standard Common Repository vs. FileMaker vs. Google BigQuery vs. Microsoft Access vs. OpenEdge

System Properties Comparison Atos Standard Common Repository vs. FileMaker vs. Google BigQuery vs. Microsoft Access vs. OpenEdge

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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.)

Application development environment with integrated database management system

Primary database model

Document store
Key-value store

Relational DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

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

www.claris.com/filemaker

cloud.google.com/bigquery

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

www.progress.com/openedge

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Atos Convergence Creators

Claris

a subsidiary of Apple

Google

Microsoft

Progress Software Corporation

Initial release

2016

1983

2010

1992

1984

Current release

1703

19.4.1, November 2021

1902 (16.0.11328.20222), March 2019

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

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

iOS

client part only
Linux
OS X
Windows

hosted

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
Solaris
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

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

but not compliant to any SQL standard

yes

close to SQL 92

APIs and other access methods

LDAP

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

none

Source-replica replication

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

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

simple rights management via user accounts and connection to external directory services

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

Users and groups

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