MongoDB – (No-SQL)

Curriculum

10 Sections
31 Lessons
10 Weeks

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Introduction to MongoDB
MongoDB is a NoSQL database that is designed for handling large volumes of unstructured or semi-structured data. Unlike traditional relational databases (RDBMS) that use tables and rows to organize data, MongoDB stores data in a flexible document-oriented format using JSON-like documents (BSON - Binary JSON). This makes it highly scalable, flexible, and performant for applications that need to handle varying types of data with complex structures.
5
MongoDB Basic Operations
MongoDB provides a rich set of basic operations for interacting with the database, including creating, reading, updating, and deleting data (often abbreviated as CRUD operations). Below are the basic operations that you can perform with MongoDB.
2
- 2.0
  Database and Collection Basics
- 2.1
  CRUD Operations
Advanced Querying Techniques
MongoDB offers a rich set of querying capabilities, and as you work with larger datasets and more complex application requirements, you’ll often need to use advanced querying techniques. These techniques help you optimize performance, execute sophisticated queries, and leverage MongoDB’s powerful indexing and aggregation features.
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Data Modeling and Schema Design
Data modeling and schema design are critical when using MongoDB (or any NoSQL database) to ensure efficient data storage, fast queries, and scalability. Unlike relational databases, MongoDB is schema-less, which means you are not required to define a fixed schema upfront. However, making the right design decisions from the beginning is essential for maintaining performance and avoid complications as your data grows.
4
Indexing and Performance Optimization
In MongoDB, indexing is a critical part of performance optimization. Without proper indexes, MongoDB has to scan every document in a collection to satisfy queries, which can be very inefficient for large datasets. Indexes are used to quickly locate data without scanning every document, making reads faster and more efficient.
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Integrating MongoDB with a Web Application (Node.js)
Integrating MongoDB with a web application built using Node.js is a common and powerful combination for building scalable and efficient web apps. MongoDB’s flexibility with JSON-like data and Node.js's asynchronous event-driven architecture work well together. In this guide, I'll walk you through the steps for integrating MongoDB with a Node.js web application, covering the essentials of setting up the connection, performing CRUD operations, and using popular libraries.
3
Security in MongoDB
Security is an essential aspect when working with MongoDB, especially when handling sensitive data in production environments. MongoDB provides a variety of security features to help protect your data against unauthorized access, injection attacks, and other vulnerabilities. Here’s a guide on securing MongoDB and your Node.js application when interacting with MongoDB.
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- 7.0
  Authentication and Authorization
- 7.1
  Data Encryption
Working with MongoDB in Production
3
Deploying and Monitoring MongoDB
Working with MongoDB in a production environment requires careful planning, attention to detail, and best practices to ensure optimal performance, security, reliability, and scalability.
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Building a Web App with MongoDB (Final Project)
Demo Project (OneStopShop)
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- 10.0
  Building the Application
- 10.1
  Final Project Features

Why MongoDB?

Flexibility:

MongoDB is great for applications that require a dynamic and evolving data structure. The schema-less nature of MongoDB allows for easy adaptation and growth, without having to redefine the structure each time new data needs to be stored.

Scalability:

MongoDB is designed to scale horizontally. This means that as your data grows, you can distribute the data across multiple servers without impacting performance. This makes it suitable for applications that need to handle big data or massive amounts of traffic.

Performance:

MongoDB provides excellent performance, particularly for read-heavy workloads. It supports efficient indexing and a powerful aggregation framework, allowing fast and flexible querying and reporting on large datasets.

Real-Time Data Processing:

MongoDB is well-suited for applications that require real-time data processing, such as analytics, logging, and event-driven systems. Its fast read and write speeds make it ideal for modern, high-velocity data-driven applications.

NoSQL Flexibility:

MongoDB is part of the NoSQL family, meaning it is not bound by the rigid structure of relational databases. This makes it ideal for handling unstructured data, such as logs, sensor data, user-generated content, and multimedia.

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What is MongoDB?