🍔 Food Delivery Database Management System (MongoDB)

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📖 Introduction

The Food Delivery Database Management System is a NoSQL database project developed using MongoDB. This project simulates a modern online food delivery platform where customers can browse restaurants, order food, make payments, and receive deliveries through riders.

The project is designed for students, beginners, and developers who want to learn MongoDB database design and implementation through a real-world application. It demonstrates proper database modeling, collection relationships, CRUD operations, aggregation pipelines, and report generation.

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🎯 Project Objectives

The main objectives of this project are:

• Design a complete food delivery database using MongoDB.
• Implement a real-world NoSQL database structure.
• Store and manage customer, restaurant, order, payment, and rider information.
• Perform CRUD operations efficiently.
• Generate useful business reports.
• Practice aggregation pipelines and data analysis.
• Understand document-based database architecture.
• Develop hands-on experience with MongoDB Compass and Mongo Shell.

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🌟 Features

✅ Complete MongoDB Database Project

✅ 6 Interconnected Collections

✅ Realistic Food Delivery Data

✅ Customer Management

✅ Restaurant Management

✅ Menu Item Management

✅ Order Tracking System

✅ Payment Processing Records

✅ Rider Management System

✅ MongoDB Aggregation Pipelines

✅ Report Generation

✅ MongoDB Compass Compatible

✅ Beginner-Friendly Structure

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🏗 System Overview

The Food Delivery System consists of six major entities:

👤 Customers

Stores customer information, contact details, city, and spending history.

🍽 Restaurants

Stores restaurant details including ratings, cuisine types, and delivery fees.

🍕 Menu Items

Contains food products available for customers to order.

📦 Orders

Maintains all order transactions and delivery statuses.

💳 Payments

Stores payment methods, payment amounts, and transaction statuses.

🛵 Riders

Manages delivery personnel information and earnings.

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🗂 Database Collections

1️⃣ Customers Collection

Stores customer information.

Sample Document

{
  "_id": ObjectId(),
  "name": "Ali Khan",
  "email": "ali@gmail.com",
  "phone": "03001234567",
  "city": "Lahore",
  "total_spent": 2500
}

Fields

Field	Description
_id	Unique Customer ID
name	Customer Name
email	Customer Email
phone	Contact Number
city	Customer City
total_spent	Total Amount Spent

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2️⃣ Restaurants Collection

Stores restaurant details.

Sample Document

{
  "_id": ObjectId(),
  "name": "Biryani House",
  "cuisine": "Pakistani",
  "rating": 4.8,
  "delivery_fee": 150,
  "is_open": true
}

Fields

Field	Description
_id	Restaurant ID
name	Restaurant Name
cuisine	Cuisine Type
rating	Customer Rating
delivery_fee	Delivery Charges
is_open	Availability Status

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3️⃣ Menu Items Collection

Stores available food items.

Sample Document

{
  "_id": ObjectId(),
  "name": "Chicken Biryani",
  "category": "Main Course",
  "price": 650,
  "restaurant": "Biryani House"
}

Fields

Field	Description
_id	Menu Item ID
name	Food Item Name
category	Food Category
price	Food Price
restaurant	Restaurant Name

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4️⃣ Orders Collection

Stores customer orders.

Sample Document

{
  "_id": ObjectId(),
  "customer_name": "Ali Khan",
  "restaurant_name": "Biryani House",
  "items": [
    "Chicken Biryani",
    "Cold Drink"
  ],
  "status": "Delivered",
  "grand_total": 800
}

Fields

Field	Description
_id	Order ID
customer_name	Customer Name
restaurant_name	Restaurant Name
items	Ordered Food Items
status	Current Status
grand_total	Final Amount

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5️⃣ Payments Collection

Stores payment records.

Sample Document

{
  "_id": ObjectId(),
  "method": "Cash",
  "amount": 800,
  "status": "Paid"
}

Fields

Field	Description
_id	Payment ID
method	Payment Method
amount	Payment Amount
status	Payment Status

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6️⃣ Riders Collection

Stores rider information.

Sample Document

{
  "_id": ObjectId(),
  "name": "Usman Ali",
  "vehicle": "Bike",
  "status": "Available",
  "earnings": 12000
}

Fields

Field	Description
_id	Rider ID
name	Rider Name
vehicle	Vehicle Type
status	Availability Status
earnings	Total Earnings

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🔗 Database Relationships

CUSTOMERS
    │
    ▼
ORDERS
    │
    ├────────► PAYMENTS
    │
    ▼
RESTAURANTS
    │
    ▼
MENU ITEMS

RIDERS
    │
    ▼
ORDERS

Relationship Summary

Relationship	Type
Customer → Orders	One-to-Many
Order → Payment	One-to-One
Restaurant → Orders	One-to-Many
Restaurant → Menu Items	One-to-Many
Rider → Orders	One-to-Many

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📊 Database Statistics

Collection	Documents
Customers	10
Restaurants	10
Menu Items	15
Orders	10
Payments	10
Riders	5

Additional Insights

• Total Revenue: ₨ 8,500+
• Delivered Orders: 7
• Preparing Orders: 2
• Out For Delivery Orders: 1
• Active Customers: 10
• Available Riders: 5
• Restaurants Across Multiple Cities
• Multiple Food Categories Available

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📁 Project Structure

FoodDelivery-Database/
│
├── README.md
│
├── data/
│   ├── customers.json
│   ├── restaurants.json
│   ├── menuitems.json
│   ├── orders.json
│   ├── payments.json
│   └── riders.json
│
├── queries/
│   ├── find_queries.txt
│   ├── update_queries.txt
│   ├── delete_queries.txt
│   └── aggregate_queries.txt
│
├── reports/
│   ├── revenue_report.txt
│   ├── customer_analysis.txt
│   ├── payment_analysis.txt
│   ├── restaurant_analysis.txt
│   └── order_status_report.txt
│
│
├── documentation/
│   └── project_documentation.pdf
│
└── LICENSE

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🚀 Installation Guide

Step 1: Install MongoDB

Download MongoDB Community Server:

https://www.mongodb.com/try/download/community

Install using the default settings.

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Step 2: Install MongoDB Compass

Download MongoDB Compass:

https://www.mongodb.com/products/compass

Install and launch MongoDB Compass.

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Step 3: Connect to MongoDB

Connection String:

mongodb://localhost:27017

Click Connect.

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Step 4: Create Database

use FoodDeliveryDB

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Step 5: Import JSON Files

Using MongoDB Compass:

1. Create Collection
2. Click Add Data
3. Select Import JSON
4. Choose File
5. Import Data

Repeat for all collections.

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🔍 Sample Queries

Find Customers from Lahore

db.customers.find({
  city: "Lahore"
})

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Find Delivered Orders

db.orders.find({
  status: "Delivered"
})

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Find Available Riders

db.riders.find({
  status: "Available"
})

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Find Top Rated Restaurants

db.restaurants.find({
  rating: {
    $gte: 4.5
  }
})

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📈 Aggregation Queries

Revenue by Restaurant

db.orders.aggregate([
{
 $group:{
   _id:"$restaurant_name",
   totalRevenue:{
     $sum:"$grand_total"
   }
 }
}
])

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Customer Spending Analysis

db.customers.aggregate([
{
 $group:{
   _id:"$city",
   totalSpent:{
     $sum:"$total_spent"
   }
 }
}
])

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Payment Method Analysis

db.payments.aggregate([
{
 $group:{
   _id:"$method",
   count:{
     $sum:1
   }
 }
}
])

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🎓 Learning Outcomes

This project demonstrates:

• MongoDB Fundamentals
• NoSQL Database Design
• Collections and Documents
• CRUD Operations
• Aggregation Pipelines
• Data Modeling
• Database Relationships
• Report Generation
• Database Analysis
• Real-World Database Development

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💼 Portfolio Benefits

This project can be used for:

• University Database Projects
• Advanced Database Lab Submission
• MongoDB Practice
• GitHub Portfolio
• Internship Applications
• Entry-Level Developer Portfolio
• Database Administrator Learning
• NoSQL Development Practice

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🛠 Technologies Used

• MongoDB
• MongoDB Compass
• JSON
• JavaScript Queries
• NoSQL Database Architecture

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🤝 Contribution

Contributions are welcome.

1. Fork the repository
2. Create a new branch
3. Commit your changes
4. Push to your branch
5. Open a Pull Request

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📜 License

This project is licensed under the MIT License.

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👨‍💻 Author

Muhammad Umar

ADP Computer Science Student

Advanced Database Management System Project

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⭐ Support

If you found this project useful:

⭐ Star the repository

🍴 Fork the repository

📢 Share with friends

💡 Suggest improvements

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🍔 Food Delivery Database Management System 🚀
Built with MongoDB for Learning and Practice.