DBMS > Microsoft Azure Cosmos DB vs. PouchDB vs. Quasardb vs. Vitess

System Properties Comparison Microsoft Azure Cosmos DB vs. PouchDB vs. Quasardb vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

pouchdb.com

quasar.ai

vitess.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

doc.quasar.ai/master

vitess.io/docs

Developer

Microsoft

Apache Software Foundation

quasardb

The Linux Foundation, PlanetScale

Initial release

2014

2012

2009

2013

Current release

7.1.1, June 2019

3.14.1, January 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0, commercial licenses available

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

JavaScript

C++

Server operating systems

hosted

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

BSD
Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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

All properties auto-indexed by default

yes

via views

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

JavaScript

View functions in JavaScript

yes

proprietary syntax

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

no user groups or roles

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