DBMS > Amazon Redshift vs. CouchDB vs. PouchDB vs. Quasardb vs. UniData,UniVerse

System Properties Comparison Amazon Redshift vs. CouchDB vs. PouchDB vs. Quasardb vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/redshift

couchdb.apache.org

pouchdb.com

quasar.ai

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

pouchdb.com/guides

doc.quasar.ai/master

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

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

Apache Software Foundation

quasardb

Rocket Software

Initial release

2012

2005

2012

2009

1985

Current release

3.3.3, December 2023

7.1.1, June 2019

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

JavaScript

C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

optional

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.

Secondary indexes

restricted

yes

via views

yes

via views

yes

with tags

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Cryptographically strong user authentication and audit trail

Access rights according to SQL-standard and operating system based

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