DBMS > atoti vs. IBM Cloudant vs. Oracle NoSQL vs. PouchDB

System Properties Comparison atoti vs. IBM Cloudant vs. Oracle NoSQL vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Database as a Service offering based on Apache CouchDB

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Object oriented DBMS

Document store

Document store
Key-value store
Relational DBMS

Document store

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

atoti.io

www.ibm.com/products/cloudant

www.oracle.com/database/nosql/technologies/nosql

pouchdb.com

Technical documentation

docs.atoti.io

cloud.ibm.com/docs/Cloudant

docs.oracle.com/en/database/other-databases/nosql-database/index.html

pouchdb.com/guides

Developer

ActiveViam

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

Apache Software Foundation

Initial release

2010

2011

2012

Current release

23.3, December 2023

7.1.1, June 2019

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

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

Java

Erlang

Java

JavaScript

Server operating systems

hosted

Linux
Solaris SPARC/x86

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

Python

View functions (Map-Reduce) in JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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