DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. Google BigQuery vs. Microsoft Access vs. Oracle Rdb

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. Google BigQuery vs. Microsoft Access vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

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

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

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.)

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

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

cloud.google.com/bigquery

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

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Atos Convergence Creators

Google

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2016

2010

1992

1984

Current release

1703

1902 (16.0.11328.20222), March 2019

7.4.1.1, 2021

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

hosted

Linux

hosted

Windows

Not a real database server, but making use of DLLs

HP Open VMS

Data scheme

yes

Schema and schema-less with LDAP views

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

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

yes

APIs and other access methods

JDBC
ODBC

LDAP

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

C
Java
Perl
Python
R

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

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

Implicit feature of the cloud service

Sharding

cell division

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

Atomic execution of specific operations

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

yes, on a single node

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

fine grained access rights according to SQL-standard

LDAP bind authentication

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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