DBMS > Amazon Redshift vs. Citus vs. Couchbase vs. Datomic vs. Percona Server for MongoDB

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

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Primary database model

Secondary database models

Document store

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

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

aws.amazon.com/redshift

www.citusdata.com

www.couchbase.com

www.datomic.com

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

Technical documentation

docs.aws.amazon.com/redshift

docs.citusdata.com

docs.couchbase.com

docs.datomic.com

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

Developer

Amazon (based on PostgreSQL)

Couchbase, Inc.

Cognitect

Percona

Initial release

2012

2010

2011

2012

2015

Current release

8.1, December 2018

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

1.0.7075, December 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

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

commercial

limited edition free

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

Java, Clojure

C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

All OS with a Java VM

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

standard, with numerous extensions

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

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java

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

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

yes

Transaction Functions

JavaScript

Triggers

yes

via the TAP protocol

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

including cross data center replication
Source-replica replication

none

But extensive use of caching in the application peers

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

Immediate Consistency

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

recommended only for testing and development

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.

Access rights for users and roles

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