DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. CouchDB vs. Vitess

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. CouchDB vs. Vitess

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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

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

aws.amazon.com/redshift

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

couchdb.apache.org

vitess.io

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

vitess.io/docs

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

The Linux Foundation, PlanetScale

Initial release

2012

2016

2005

2013

Current release

1703

3.3.3, December 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0, commercial licenses available

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

Erlang

Server operating systems

hosted

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

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

restricted

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

LDAP

RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

atomic operations within a single document possible

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

LDAP bind authentication

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

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