DBMS > Amazon DocumentDB vs. Drizzle vs. IBM Cloudant vs. OushuDB

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. IBM Cloudant vs. OushuDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Database as a Service offering based on Apache CouchDB

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

aws.amazon.com/documentdb

www.ibm.com/products/cloudant

www.oushu.com/product/oushuDB

Technical documentation

aws.amazon.com/documentdb/resources

cloud.ibm.com/docs/Cloudant

www.oushu.com/documentation

Developer

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oushu

Initial release

2019

2008

2010

Current release

7.2.4, September 2012

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

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++

Erlang

Server operating systems

hosted

FreeBSD
Linux
OS X

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

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

SQL

Support of SQL

yes

with proprietary extensions

Full-featured ANSI SQL support

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Hadoop integration

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

yes

Transaction concepts

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

Atomic single-document operations

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users and roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

Kerberos, SSL and role based access

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