DBMS > Amazon Redshift vs. CouchDB vs. MonetDB vs. TerminusDB vs. Warp 10

System Properties Comparison Amazon Redshift vs. CouchDB vs. MonetDB vs. TerminusDB vs. Warp 10

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.

A relational database management system that stores data in columns

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

Document store
RDF store

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Trend Chart

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

www.monetdb.org/Documentation

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

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

MonetDB BV

DataChemist Ltd.

SenX

Initial release

2012

2005

2004

2018

2015

Current release

3.3.3, December 2023

Dec2023 (11.49), December 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Mozilla Public License 2.0

Open Source

GPL V3

Open Source

Apache License 2.0

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

Prolog, Rust

Java

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

restricted

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

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

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

yes, in SQL, C, R

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding via remote tables

Graph Partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

Journaling Streams

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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