DBMS > Amazon Redshift vs. Couchbase vs. MonetDB vs. Percona Server for MongoDB

System Properties Comparison Amazon Redshift vs. Couchbase vs. MonetDB vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A relational database management system that stores data in columns

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

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
Spatial DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	18.46
Rank	#36	Overall
	#5	Document stores

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	0.55
Rank	#253	Overall
	#39	Document stores

Website

aws.amazon.com/redshift

www.couchbase.com

www.monetdb.org

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.aws.amazon.com/redshift

docs.couchbase.com

www.monetdb.org/Documentation

docs.percona.com/percona-distribution-for-mongodb

Developer

Amazon (based on PostgreSQL)

Couchbase, Inc.

MonetDB BV

Percona

Initial release

2012

2011

2004

2015

Current release

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

Dec2023 (11.49), December 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Mozilla Public License 2.0

Open Source

GPL Version 2

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

C, C++, Go and Erlang

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

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

yes, in SQL, C, R

JavaScript

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

none

Source-replica replication available in experimental status

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

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

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

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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