DBMS > Amazon DocumentDB vs. ClickHouse vs. CouchDB vs. Graph Engine vs. IBM Cloudant

System Properties Comparison Amazon DocumentDB vs. ClickHouse vs. CouchDB vs. Graph Engine vs. IBM Cloudant

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Database as a Service offering based on Apache CouchDB

Primary database model

Document store

Relational DBMS

Document store

Graph DBMS
Key-value store

Document store

Secondary database models

Time Series DBMS

Spatial DBMS

using the Geocouch extension

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

aws.amazon.com/documentdb

clickhouse.com

couchdb.apache.org

www.graphengine.io

www.ibm.com/products/cloudant

Technical documentation

aws.amazon.com/documentdb/resources

clickhouse.com/docs

docs.couchdb.org/en/stable

www.graphengine.io/docs/manual

cloud.ibm.com/docs/Cloudant

Developer

Clickhouse Inc.

Apache Software Foundation

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

Microsoft

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2019

2016

2005

2010

Current release

v24.3.2.23-lts, April 2024

3.3.3, December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

MIT License

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

C++

Erlang

.NET and C

Erlang

Server operating systems

hosted

FreeBSD
Linux
macOS

Android
BSD
Linux
OS X
Solaris
Windows

.NET

hosted

Data scheme

schema-free

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

yes

via views

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

RESTful HTTP/JSON API

RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

C#
C++
F#
Visual Basic

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

improved architecture with release 2.0

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

atomic operations within a single document possible

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Optimistic locking

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights for users and roles

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per database

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