Introduction to MongoDB

Speaker

• Name: Jesse Hall
• Role: Senior Developer Advocate at MongoDB
• Alias: Known on YouTube as Code Stacker

Agenda

1. Document Database Basics
2. Create a Free MongoDB Atlas Cluster
3. Load Data into Cluster (from JSON file)
4. Clone an E-commerce Project
5. Connect the App to MongoDB Atlas

Key Concepts

Relational Databases (SQL)

• Data is stored in rows and columns (like spreadsheets)
• Related data is stored in separate tables to avoid duplication
• Example: users table and phone numbers table
• Requires joining tables to query related data

Document Databases (MongoDB)

• Stores data in JSON documents
• Stores data in key-value pairs; supports various data types (strings, numbers, booleans, arrays, nested objects)
• Stores related data in the same document (no need for separate collections)
• Key Principle: Data accessed together should be stored together -> Faster queries

Terminology

• Database: Same in both relational and document databases
• Table (SQL) = Collection (MongoDB)
• Row (SQL) = Document (MongoDB)
• Column (SQL) = Field (MongoDB)

Accessing Data in MongoDB

MongoDB Query API

• Query and update documents using powerful operations ($updateMany, $set)
• Indexing: Optimize queries with various index types (compound, multi-key, wildcard, geospatial, etc.)
• Transformation & Analysis: Create real-time analytics, deploy full-text search, and perform graph operations
• Join & Union: Use aggregation stages like $lookup and $unionWith

Query Examples

• SQL: SELECT * FROM people
• MongoDB: db.people.find({})
• SQL: SELECT * FROM people WHERE age = 25
• MongoDB: db.people.find({ age: 25 })
• SQL: SELECT * FROM people WHERE age > 25
• MongoDB: db.people.find({ age: { $gt: 25 } })*

Client Drivers

• Available for various languages (e.g., C#, Go, Java, Node.js, Python, etc.)

Live Demo

Steps

1. Create MongoDB Atlas Account
   • Option: Free forever tier
2. Build a New Database
   • Types: Serverless, Dedicated, Shared (Free)
   • Provider: AWS, Google Cloud, or Azure
   • Create Cluster
3. Set Up Access
   • Create user (e.g., username: admin, password: super-secret)
   • Add IP address to access list
4. Clone E-commerce Repo
   • Load sample data (products.json)

Using MongoDB Compass

• Purpose: GUI for MongoDB
• Connection String: Get from MongoDB Atlas
• Import Data: Upload JSON file (e.g., products.json)

Application Setup (VS Code)

1. Clone Repository
2. Switch to Specific Branch (quick-demo)
3. Install Dependencies (npm install)
4. Configure Environment Variables
   • File: .env.local with MongoDB URI
5. Run Application (npm run dev)
6. View on localhost:3000
7. Fetch Products Data
   • Connects to MongoDB, pulls products, and displays them

MongoDB Connection in Code

• File: lib/mongodb.js
• Usage: Returns client promise for database operations

Server-Side Data Fetching (Next.js)

• File: pages/index.js
• Function: getServerSideProps
  • Connects to DB, fetches products collection, returns data to component

Testing Query Changes

• Example: Fetch only products with category Hoodie
  • Modify find query with { category: 'Hoodie' }

Conclusion

• MongoDB setup, data loading, connection to app, and data fetching demo