DBMS > Atos Standard Common Repository vs. Couchbase vs. Microsoft Azure SQL Database vs. mSQL vs. SAP SQL Anywhere

System Properties Comparison Atos Standard Common Repository vs. Couchbase vs. Microsoft Azure SQL Database vs. mSQL vs. SAP SQL Anywhere

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Database as a Service offering with high compatibility to Microsoft SQL Server

mSQL (Mini SQL) is a simple and lightweight RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

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

www.couchbase.com

azure.microsoft.com/en-us/products/azure-sql/database

hughestech.com.au/products/msql

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.couchbase.com

docs.microsoft.com/en-us/azure/azure-sql

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Atos Convergence Creators

Couchbase, Inc.

Microsoft

Hughes Technologies

SAP

formerly Sybase

Initial release

2016

2011

2010

1994

1992

Current release

1703

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

V12

4.4, October 2021

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

free licenses can be provided

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, C++, Go and Erlang

C++

Server operating systems

Linux

Linux
OS X
Windows

hosted

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

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

A subset of ANSI SQL is implemented

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

yes

APIs and other access methods

LDAP

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Transact SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes, with always 3 replicas available

none

Source-replica replication

Database mirroring

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

none

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

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

Ephemeral buckets

yes

User concepts

Access control

LDAP bind authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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