DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. Linter vs. Microsoft Access vs. Stardog

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. Linter vs. Microsoft Access vs. Stardog

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service for use with business intelligence tools

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

RDBMS for high security requirements

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.)

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/redshift

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

linter.ru

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

www.stardog.com

Technical documentation

docs.aws.amazon.com/redshift

developer.microsoft.com/en-us/access

docs.stardog.com

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

relex.ru

Microsoft

Stardog-Union

Initial release

2012

2016

1990

1992

2010

Current release

1703

1902 (16.0.11328.20222), March 2019

7.3.0, May 2020

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

hosted

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Windows

Not a real database server, but making use of DLLs

Linux
macOS
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

but not compliant to any SQL standard

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

LDAP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
DAO
ODBC
OLE DB

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

since Access 2010 using the ACE-engine

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

since Access 2010 using the ACE-engine

yes

via event handlers

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

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

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

fine grained access rights according to SQL-standard

LDAP bind authentication

fine grained access rights according to SQL-standard

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

Access rights for users and roles

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