DBMS > Atos Standard Common Repository vs. IBM Db2 vs. Microsoft SQL Server vs. Riak KV

System Properties Comparison Atos Standard Common Repository vs. IBM Db2 vs. Microsoft SQL Server vs. Riak KV

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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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

Primary database model

Document store
Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

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

www.ibm.com/products/db2

www.microsoft.com/en-us/sql-server

Technical documentation

www.ibm.com/docs/en/db2

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Atos Convergence Creators

IBM

Microsoft

OpenSource, formerly Basho Technologies

Initial release

2016

1983

host version

1989

2009

Current release

1703

12.1, October 2016

SQL Server 2022, November 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

free version is available

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Erlang

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

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

restricted

SQL

Support of SQL

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

only with Windows/Unix/Linux Version

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

yes, using Riak Security

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