MongoDB is an open source, document-oriented, NoSql database whose data is stored in an organized format. It is scalable and easy to learn, commonly used in modern web and mobile apps, dealing with high volumes of data. MongoDB stores data in BSON format, which lets you store JSON like documents efficiently.
This architecture is very well adapted to unstructured or semi-structured data. MongoDB is a great choice to use in applications where you need to support a dynamic schema designs. MongoDB is open-source and is available for free in Linux, Windows, and macOS systems.
This MongoDB tutorial is designed for both beginners and experienced professionals and it covers basic to advanced MongoDB topics. Before starting MongoDB, some prerequisite knowledge of Databases, Frontend development, Text editor and execution of programs, etc would be beneficial in upcoming discussion.
Why Learn MongoDB?
Developers use MongoDB because it offers a lot of features for those who like to work with big data. Here are few key reasons of why you should learn MongoDB
- MongoDB is a popular technology for modern web development, particularly high-traffic websites and real-time analytics.
- It provides scalability through sharding and also supports high availability through replication.
- MongoDB can be easily paired with various programming languages such as JavaScript (Node.js), Python, Java and more.
- General corporations like eBay, Uber and Adobe use MongoDB while processing big, unstructured data.
- It offers greater flexibility and faster development time through its schema-less nature.
MongoDB Hello World Example
The first step to start with MongoDB is to Insert a simple document into a database using MongoDB's Node.js driver. This example shows you have MongoDB installed and running locally.
XML
// MongoDB Hello World Program
const { MongoClient } = require('mongodb');
// Connection URL
const url = 'mongodb://localhost:27017';
const client = new MongoClient(url);
async function run() {
try {
// Connect to the MongoDB server
await client.connect();
// Choose the database
const db = client.db('testdb');
// Choose the collection
const collection = db.collection('users');
// Insert a document
const result = await collection.insertOne({ name: "John Doe", age: 30 });
console.log(`Document inserted with _id: ${result.insertedId}`);
} finally {
// Close the connection
await client.close();
}
}
run().catch(console.error);
Output:
Document inserted with _id: [ObjectId]
Introduction to MongoDB
In this section you will explore the core concepts, functionalities, and advantages over traditional relational databases. Unleash the potential of flexible data modeling for modern applications.
Installation and Setup
Here in this section you will learn how to setting up MongoDB, a powerful NoSQL database. Here you will get a full details on installation process and essential configuration steps to get your MongoDB on various OS. Follow along to establish a strong foundation for your MongoDB applications.
Basics of MongoDB
This section of MongoDB tutorial breaks down core concepts like documents, collections, and queries. We'll explore how MongoDB stores and retrieves data, empowering you to harness its flexibility for modern application development.
Navigating and managing your MongoDB data is a breeze with its diverse toolkit. So, here in this section, you will explore the official interfaces like MongoDB Compass and the command-line shell, empowering you to interact with your database effectively. This section equips you with the tools to unleash MongoDB's potential.
CRUD Operations in MongoDB
In this section we will explores CRUD operations, Create, Read, Update, and Delete. Learn how to effectively insert, retrieve, modify, and remove documents within your MongoDB collections. This empowers you to manage your database with precision.
Insert Operations
Update Operations
Delete Operations
Query Operations
MongoDB Operators
MongoDB operators are like magic wands for your data! Throug this section we will let you into these operators that let you filter, sort, and transform your documents with ease. Grasp these tools to craft powerful queries, unleashing the true potential of your MongoDB database.
Comparison Operators
Logical Operators
Arithmetic Operators
Field Update Operators
Array Expression Operators
Array Update Operators
String Expression Operators
Aggregation
Supercharge your data analysis with MongoDB Aggregation! This section delves into crafting powerful pipelines that transform and summarize your collections. Learn to group documents, calculate values, and uncover hidden insights within your MongoDB data.
Indexing
This section delves into creating and leveraging indexes, specialized data structures that significantly improve retrieval efficiency. Learn how to identify ideal fields for indexing and optimize your database performance for faster results.
Transactions and Data Modeling
MongoDB offers flexibility with its document model, but transactions come into play for ensuring data consistency across multiple updates. This section clarifies when to leverage MongoDB's atomic writes on single documents and dives into multi-document transactions for complex operations. We'll guide you on optimizing your data model for both efficiency and data integrity.
Replication and Sharding
This section delves into replication and sharding, two techniques for boosting performance and ensuring data availability. Learn how to create fault-tolerant backups and distribute data across multiple servers for a scalable and resilient MongoDB deployment.
Security
This section tackles the essential security measures to safeguard your database. We'll delve into access control, encryption strategies, and auditing practices to fortify your MongoDB environment and ensure data confidentiality. Follow these best practices to build a robust security posture for your MongoDB deployments.
MongoDB Quiz & Interview
Prepare for MongoDB interviews with these commonly asked questions, covering core concepts like CRUD operations, indexing, aggregation, data modeling and more:
MongoDB Applications and Projects
Dive into the exciting world of what you can build with MongoDB! We'll showcase real-world applications that leverage MongoDB's flexibility and explore project ideas to ignite your development journey. Get inspired to create scalable and dynamic applications with MongoDB!
Difference Between MongoDB and MySQL
| Feature | MongoDB | MySQL |
|---|
| Data Model | Document-oriented (JSON-like BSON) | Relational (tables with rows and columns) |
| Schema | Schema-less, flexible | Schema-based, structured |
| Scalability | Horizontal scaling (sharding) | Vertical scaling |
| Transactions | Supports multi-document ACID transactions (since v4.0) | Supports ACID transactions |
| Query Language | MongoDB Query Language (MQL) | Structured Query Language (SQL) |
| Data Storage | Stores data in collections of documents | Stores data in tables |
| Indexing | Supports various types of indexes | Supports various types of indexes |
| Performance | Generally faster for read/write operations in large datasets | Generally reliable and consistent performance |
| Use Cases | Best for hierarchical data, real-time analytics, content management | Best for structured data, transactional applications |
| Join Operations | Limited support for joins, typically done in application logic | Full support for joins between tables |
| Replication | Replica sets for high availability and redundancy | Master-slave replication, Group Replication |
| Flexibility | Highly flexible, easily adapts to changing requirements | Less flexible, schema changes require careful planning |
| Support for Unstructured Data | Excellent, can store any type of data in a document | Limited, primarily structured data |
Career & Jobs in MongoDB
MongoDB is a leading NoSQL database with growing demand across industries. It offers career opportunities in data management, cloud systems, and application development, with roles such as backend developers, cloud engineers, and database administrators.
| Career | Average Salary (INR) | Average Salary (USD) |
|---|
| MongoDB Developer | ₹7,00,000 – ₹18,00,000 | $70,000 – $130,000 |
| Database Administrator (DBA) | ₹6,00,000 – ₹15,00,000 | $65,000 – $120,000 |
| Full Stack Developer | ₹8,00,000 – ₹20,00,000 | $80,000 – $150,000 |
| Backend Engineer | ₹8,50,000 – ₹22,00,000 | $90,000 – $160,000 |
| Data Engineer | ₹10,00,000 – ₹25,00,000 | $100,000 – $180,000 |
| Cloud Engineer | ₹12,00,000 – ₹30,00,000 | $110,000 – $200,000 |
| Software Engineer | ₹7,50,000 – ₹18,00,000 | $75,000 – $130,000 |
| Solutions Architect | ₹15,00,000 – ₹40,00,000 | $150,000 – $250,000 |
| DevOps Engineer | ₹10,00,000 – ₹20,00,000 | $100,000 – $150,000 |
| MongoDB Consultant | ₹12,00,000 – ₹30,00,000 | $110,000 – $200,000 |
List of Companies using MongoDB
These are some Popular companies that use MongoDB in their workflow:
| Company Name | MongoDB Implementation |
|---|
| eBay | Utilizes MongoDB for search suggestions and internal cloud management. |
| Adobe | Uses MongoDB for scalable data storage in creative cloud applications. |
| Uber | Integrates MongoDB to manage real-time geolocation and ride data. |
| Verizon | Adopts MongoDB for high-performance data handling in telecommunications. |
| MetLife | Uses MongoDB to build a 360-degree customer view in its "The Wall" application. |
| Forbes | Employs MongoDB for content management and real-time analytics. |
| Shutterfly | Utilizes MongoDB to store and manage billions of photos for its users. |
| Codecademy | Integrates MongoDB to handle user progress and course data efficiently. |
| CERN | Uses MongoDB in the Large Hadron Collider for data aggregation purposes. |
| Foursquare | Uses MongoDB on AWS to manage location data and user check-ins. |
