DBMS > atoti vs. CouchDB vs. DataFS vs. Microsoft Azure Cosmos DB

System Properties Comparison atoti vs. CouchDB vs. DataFS vs. Microsoft Azure Cosmos DB

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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.

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Object oriented DBMS

Document store

Object oriented DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

atoti.io

couchdb.apache.org

newdatabase.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.atoti.io

docs.couchdb.org/en/stable

dev.mobiland.com/Overview.xsp

learn.microsoft.com/azure/cosmos-db

Developer

ActiveViam

Apache Software Foundation

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

Mobiland AG

Microsoft

Initial release

2005

2018

2014

Current release

3.3.3, December 2023

1.1.263, October 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache version 2

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

Java

Erlang

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Windows

hosted

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

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

.Net
C
C#
C++
VB.Net

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

Python

View functions in JavaScript

JavaScript

Triggers

yes

no, except callback-events from server when changes happened

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

improved architecture with release 2.0

Proprietary Sharding system

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

strategy: 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.

yes

User concepts

Access control

Access rights for users can be defined per database

Windows-Profile

Access rights can be defined down to the item level

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