DBMS > Microsoft Azure Cosmos DB vs. OpenSearch

System Properties Comparison Microsoft Azure Cosmos DB vs. OpenSearch

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Our visitors often compare Microsoft Azure Cosmos DB and OpenSearch with PostgreSQL, MongoDB and Microsoft Azure AI Search.

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Search engine
Vector DBMS

Secondary database models

Spatial DBMS

Vector DBMS

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

Score	22.94
Rank	#26	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#2	Wide column stores

Score	17.38
Rank	#32	Overall
	#4	Search engines
	#2	Vector DBMS

Website

azure.microsoft.com/services/cosmos-db

github.com/opensearch-project
opensearch.org

Technical documentation

learn.microsoft.com/azure/cosmos-db

opensearch.org/docs/latest

Developer

Microsoft

The OpenSearch Software Foundation

Initial release

2014

2021

Current release

2.19, February 2025

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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.

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Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

yes

JSON types

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

Supported programming languages

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Access rights can be defined down to the item level

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More resources

Recent citations in the news

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