๐Ÿ“˜ How to Use MongoDB in VS Code


✨ Introduction

MongoDB is a popular NoSQL, document-oriented database designed for modern application development. Instead of storing data in rows and columns (like SQL), MongoDB stores it in flexible, JSON-like documents, making it ideal for real-time analytics, scalable systems, and agile development.


On the other hand, Visual Studio Code (VS Code) is a lightweight but powerful source code editor available for Windows, macOS, and Linux. It comes with built-in support for JavaScript, Node.js, and has a rich ecosystem of extensions — one of which is the MongoDB extension.


In this blog, we’ll walk you through how to use MongoDB in VS Code, from setup to executing queries, with visual guidance at every step.


๐Ÿ”ง Prerequisites

Before we begin, ensure you have the following:


✅ MongoDB Atlas Account (or local MongoDB server installed)


✅ VS Code installed on your system


✅ MongoDB for VS Code extension


✅ A connection string (from MongoDB Atlas if using cloud)


๐Ÿชœ Step-by-Step Guide

Step 1: Install the MongoDB Extension in VS Code

Open Visual Studio Code


Go to the Extensions panel on the sidebar (or press Ctrl + Shift + X)


Search for "MongoDB for VS Code" by MongoDB Inc.


Click Install 



Step 2: Connect to MongoDB

After installation, click the MongoDB leaf icon in the Activity Bar on the left (sidebar)


Click on "Connect"


Paste your MongoDB URI connection string (from MongoDB Atlas or your local server)


Click Connect





๐Ÿ“ Tip: You can find the connection string in MongoDB Atlas → Database → Connect → VS Code.


Step 3: Explore Your Databases

Once connected:


All databases in your cluster will appear in the sidebar


Expand a database to see collections


Click on a collection to view documents


Step 4: Run MongoDB Commands in Playground

Click “Playground” from the MongoDB sidebar or Ctrl + Shift + P → “MongoDB: Create Playground”


Write your MongoDB queries like:


js

Copy

Edit

use("blogDB")


db.posts.insertOne({

  title: "First Blog Post",

  author: "Sanket",

  views: 100

});

Click Play ▶ to run it.


๐Ÿ” Additional Features

๐Ÿ”„ Auto-complete for MongoDB Shell commands


๐Ÿ’ก Syntax highlighting


๐Ÿ“ Edit documents directly from VS Code


๐Ÿ“ฆ Manage indexes and collections visually


๐Ÿ” Supports both cloud and local MongoDB connections


✅ Bonus: Get Connection String from MongoDB Atlas

Go to https://cloud.mongodb.com


Click on your project


Go to Database → Click Connect


Choose VS Code, copy the URI string


๐Ÿ Conclusion

By following the steps above, you can integrate MongoDB into VS Code for a seamless development experience. Whether you're testing queries or managing collections, the MongoDB for VS Code extension is a game-changer for developers — especially for rapid prototyping and full-stack applications. 

Sanket Chavan(BCA2302234)

University: Shree Balaji University, Pune

School: School of Computer Studies

Course: BCA (Bachelor of Computer Applications)

Interests: NoSQL, MongoDB, and related technologies

๐Ÿ“ธ Instagram ๐Ÿ”— LinkedIn ๐ŸŒ Official Website

Comments

Post a Comment

Popular posts from this blog

Query Operator's

Image
  MongoDB Blog: Query Operators ($gt,$lt,$in,$or,) Introduction :-   In MongoDB, query operators make it easy to filter, match, and retrieve specific documents from a collection. They enhance the power of find() by allowing us to compare values, check for inclusion, perform logical operations. MongoDB is a flexible, document-oriented NoSQL database, and one of its biggest strengths is the ability to query data in a powerful and dynamic way . Instead of relying on rigid SQL statements, MongoDB uses query operators to filter, match, and manipulate documents stored in collections. Common categories include :-  Comparison Operators – $gt , $lt , $gte , $lte , $eq , $ne Logical Operators – $or , $and , $not , $nor Element Operators – $exists , $type Array Operators – $in , $nin , $all , $size 1. Comparison Operators:-  In MongoDB, comparison operators are used within queries to filter documents based on how field values relate to specific criteria, allowing you to ...
Read more

Creating Documents in MongoDB(Insert)

Image
        Creating Documents in MongoDB(Insert) MongoDB is a powerful, flexible, and scalable NoSQL database used for managing large volumes of unstructured and semi-structured data. Unlike traditional relational databases, MongoDB uses a document-based data model where data is stored in BSON (Binary JSON) format, allowing for nested documents and arrays. Creating documents is the fundamental step in building a MongoDB collection. Documents are inserted into collections using specific commands such as insertOne() for a single document and insertMany() for multiple documents. These operations allow users to add new records with ease, providing a dynamic and schema-less structure that suits modern applications.  Explanation In MongoDB, a document is a record in a collection. Documents are stored in BSON (Binary JSON) format. When we want to add new data to a collection, we use insert operations. There are three primary methods to insert documents: insertO...
Read more
Image
TTL(Time To Live) Indexes - Set It and Forget It!   In the world of modern web and mobile applications, data is constantly being generated — some of it permanent, much of it temporary. Think about one-time passwords (OTPs), user session tokens, verification links, or cached search results. These are all types of data that should not live forever. Imagine you're building a system that sends OTPs valid for 5 minutes. If you don’t clean up expired OTPs, your database will keep growing unnecessarily, leading to bloated storage and slower queries. Writing custom cleanup scripts or cron jobs for each scenario isn't just tedious — it's inefficient. That’s where MongoDB TTL (Time-To-Live) Indexes step in. They provide a built-in, automatic mechanism to delete documents after a set time — with no manual work required. TTL Indexes help keep your database clean, fast, and resource-friendly. MongoDB TTL Indexes A TTL (Time-To-Live) Index in MongoDB allows you ...
Read more