tutorial-delete.md

title	description	author	ms.author	ms.service	ms.subservice	ms.topic	ms.date
Deleting Data into Cosmos DB for MongoDB	Learn how to get started with deleting data in Cosmos DB for MongoDB.	gahl-levy	gahllevy	azure-cosmos-db	mongodb	tutorial	01/24/2023

Deleting Data into Cosmos DB for MongoDB

One of the most basic operations is deleting data in a collection. In this guide, we will cover everything you need to know about deleting data using the Mongo Shell (Mongosh).

Understanding the deleteOne() and deleteMany() Methods

The most common way to delete data in MongoDB is to delete individual documents from a collection. You can do this using the deleteOne() or deleteMany() method.

The deleteOne() method is used to delete a single document from a collection that matches a specific filter. For example, if you wanted to delete a user with the name "John Doe" from the "users" collection, you would use the following command:

db.users.deleteOne({ "name": "John Doe" })

The deleteMany() method, on the other hand, is used to delete multiple documents from a collection that match a specific filter. For example, if you wanted to delete all users with an age less than 30 from the "users" collection, you would use the following command:

db.users.deleteMany({ "age": { $lt: 30 } })

It's important to note that both of these methods return an object with the following properties:

deletedCount: The number of documents deleted. acknowledged: This property will be true.

Deleting a Collection

To delete an entire collection, use the drop() method. For example, if you wanted to delete the "users" collection, you would use the following command:

db.users.drop()
This will delete the "users" collection and all of its documents permanently.

Next steps

• Learn how to use Studio 3T with Azure Cosmos DB for MongoDB.
• Learn how to use Robo 3T with Azure Cosmos DB for MongoDB.
• Explore MongoDB samples with Azure Cosmos DB for MongoDB.
• Trying to do capacity planning for a migration to Azure Cosmos DB? You can use information about your existing database cluster for capacity planning.
  • If all you know is the number of vCores and servers in your existing database cluster, read about estimating request units using vCores or vCPUs.
  • If you know typical request rates for your current database workload, read about estimating request units using Azure Cosmos DB capacity planner.