mongodb full Course

MongoDB HOME

Welcome to the MongoDB tutorial! This tutorial will guide you through MongoDB's basic operations and concepts.

MongoDB Get Started

MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. In this section, we will cover the installation process.

MongoDB Query API

The MongoDB Query API provides methods to query the database, find documents, and update or delete them based on criteria.

MongoDB Create DB

Learn how to create a database in MongoDB using the `use` command or by inserting data into a collection.


db = connect("mongodb://localhost:27017/mydatabase");
    

MongoDB Collection

MongoDB stores data in collections, which are analogous to tables in relational databases. Here's how to create a collection:


db.createCollection("users");
    

MongoDB Insert

Learn how to insert data into a collection using the `insertOne()` or `insertMany()` methods.


db.users.insertOne({ name: "John Doe", age: 30 });
    

MongoDB Find

Use the `find()` method to query a collection and retrieve documents based on specific conditions.


db.users.find({ age: { $gt: 25 } });
    

MongoDB Update

Update documents in a collection with the `updateOne()`, `updateMany()`, or `replaceOne()` methods.


db.users.updateOne({ name: "John Doe" }, { $set: { age: 31 } });
    

MongoDB Delete

Learn how to delete documents using the `deleteOne()` and `deleteMany()` methods.


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

MongoDB Query Operators

MongoDB provides several query operators to filter documents. These include `$gt`, `$lt`, `$eq`, `$in`, and more.


db.users.find({ age: { $gt: 20, $lt: 30 } });
    

MongoDB Update Section

Learn how to perform advanced updates in MongoDB, including using the `$set`, `$unset`, `$inc` operators, and more.


db.users.updateOne({ name: "John Doe" }, { $inc: { age: 1 } });
    

MongoDB Operators

MongoDB provides various operators like comparison operators ($gt, $lt, etc.), logical operators ($and, $or), and array operators to filter data.

MongoDB Aggregations

MongoDB aggregation framework is used to process data and return computed results. It is commonly used for data analysis and transformation.

MongoDB $group

The `$group` operator is used to group documents by a specified expression and perform aggregation operations on each group.


db.orders.aggregate([
    { $group: { _id: "$customer_id", totalAmount: { $sum: "$amount" } } }
]);
    

MongoDB $limit

The `$limit` operator is used to restrict the number of documents returned in the aggregation pipeline.


db.orders.aggregate([
    { $limit: 5 }
]);
    

MongoDB $project

The `$project` operator is used to include, exclude, or add new fields to the documents in the aggregation pipeline.


db.orders.aggregate([
    { $project: { _id: 0, customer_id: 1, amount: 1 } }
]);
    

MongoDB $sort

The `$sort` operator is used to sort documents in the aggregation pipeline based on one or more fields.


db.orders.aggregate([
    { $sort: { amount: -1 } }
]);
    

MongoDB $match

The `$match` operator is used to filter documents that meet a specific condition.


db.orders.aggregate([
    { $match: { status: "completed" } }
]);
    

MongoDB $addFields

The `$addFields` operator is used to add new fields to documents in the aggregation pipeline.


db.orders.aggregate([
    { $addFields: { discount: { $multiply: ["$amount", 0.1] } } }
]);
    

MongoDB $count

The `$count` operator is used to count the number of documents that match the specified condition.


db.orders.aggregate([
    { $count: "totalOrders" }
]);
    

MongoDB $lookup

The `$lookup` operator allows you to join documents from another collection.


db.orders.aggregate([
    { $lookup: { from: "customers", localField: "customer_id", foreignField: "_id", as: "customer_info" } }
]);
    

MongoDB $out

The `$out` operator is used to write the results of an aggregation pipeline to a new collection.


db.orders.aggregate([
    { $match: { status: "completed" } },
    { $out: "completed_orders" }
]);
    

MongoDB Indexing/Search

Indexes improve the efficiency of searches in MongoDB. You can create indexes on fields that are frequently used in queries.


db.orders.createIndex({ customer_id: 1 });
    

MongoDB Validation

MongoDB supports schema validation, allowing you to enforce rules on your documents when inserting or updating data.


db.createCollection("orders", {
    validator: {
        $jsonSchema: {
            bsonType: "object",
            required: ["customer_id", "amount"],
            properties: {
                customer_id: { bsonType: "int" },
                amount: { bsonType: "double" }
            }
        }
    }
});
    

MongoDB Data API

The MongoDB Data API allows you to interact with MongoDB through HTTP endpoints for ease of integration with web apps and services.

MongoDB Drivers

MongoDB provides official drivers for various programming languages, enabling easy integration into your application.

MongoDB Node.js Driver

The MongoDB Node.js driver is a native JavaScript driver that provides a simple API for interacting with MongoDB from Node.js applications.


const { MongoClient } = require('mongodb');
MongoClient.connect('mongodb://localhost:27017')
    .then(client => {
        const db = client.db('mydatabase');
        // Further operations
    });
    

MongoDB Charts

MongoDB Charts is a fully managed data visualization tool that allows you to create visualizations and dashboards based on your MongoDB data. You can create charts to explore and analyze your data in a graphical way without the need for complex queries or external tools.

With MongoDB Charts, you can visualize your MongoDB data in various chart types, including bar charts, line graphs, scatter plots, pie charts, and more. It is integrated directly with MongoDB Atlas, which allows for seamless data access and integration.

Features of MongoDB Charts

Basic Example: Creating a Chart

To create a chart in MongoDB Charts, follow these basic steps:

  1. Log in to MongoDB Atlas and go to the Charts section.
  2. Create a new chart by selecting a collection from your database.
  3. Choose the chart type (e.g., bar, line, pie).
  4. Drag the fields you want to analyze into the appropriate axes or labels.
  5. Adjust the settings to customize the chart (e.g., axis titles, legend, etc.).
  6. Click "Save" to store your chart and add it to a dashboard.

Example Chart Types

Here are some common chart types in MongoDB Charts:

MongoDB Exercises

MongoDB Exercises offer hands-on practice for learners to apply their knowledge of MongoDB in real-world scenarios. By completing exercises, you can strengthen your understanding of MongoDB concepts such as CRUD operations, aggregation, indexing, and more.

These exercises are designed to test your ability to work with MongoDB databases, collections, and documents, while also challenging you to solve problems using MongoDB’s powerful features.

Example Exercises

How to Solve MongoDB Exercises

To solve MongoDB exercises:

  1. Set up a MongoDB database, either locally or using MongoDB Atlas.
  2. Work with the MongoDB shell or MongoDB Compass to interact with the database.
  3. Write queries using MongoDB's syntax to manipulate and retrieve data.
  4. Test your queries and check whether they return the expected results.
  5. Complete all exercises and ensure you have a strong grasp of the core MongoDB operations.

MongoDB Certificate

Upon completing MongoDB-related courses and exercises, you can earn a MongoDB certificate. The certificate validates your knowledge and skills in working with MongoDB and is a valuable addition to your resume.

How to Obtain MongoDB Certification

To earn your MongoDB certification:

  1. Sign up for MongoDB University and enroll in a course.
  2. Complete the course, including quizzes, assignments, and exercises.
  3. Take the final exam, which tests your knowledge of MongoDB concepts and practical skills.
  4. Upon passing the exam, you will receive a digital certificate of completion.

Benefits of MongoDB Certification