Hotel Reservation (AirBnb, Booking.com) - System Design Interview Question

Summary

This video delves into the key challenges of designing a hotel booking system, like those used by platforms such as Airbnb and Booking.com. It covers essential aspects such as hotel management, user reservations, search functionality, and notification systems, while ensuring data consistency and low latency. The video explores the core data model and API design, including the flow of adding hotels and making reservations. Key design principles such as avoiding double bookings, handling concurrency, and scaling the system using technologies like Kafka and Elasticsearch are discussed. The video also touches on error handling, payment processing, and monitoring strategies for a robust system.

Takeaways

• 😀 Efficient hotel booking systems must ensure no double bookings across thousands of accommodations worldwide.
• 😀 Hotel managers should be able to add/remove hotels and rooms, update prices, and manage availability through a centralized system.
• 😀 Users should be able to search hotels and rooms based on filters like location, price, and check-in/check-out dates.
• 😀 The system must provide users with reservation creation, cancellation options, and access to past reservation history.
• 😀 Consistency and low latency are crucial for handling concurrent requests and ensuring a smooth user experience.
• 😀 A basic hotel reservation system data model includes tables for users, hotels, room types, room inventory, pricing, reservations, and notifications.
• 😀 The API design for the booking system uses RESTful principles, with endpoints for adding hotels, adding room types, searching for rooms, and making reservations.
• 😀 In the hotel addition flow, a hotel manager submits a POST request with details, which triggers various backend processes like image uploading, message queues, and database updates.
• 😀 For reservation creation, the system prevents double bookings using techniques like item potency keys, serializable isolation levels, and row-level locking.
• 😀 Key system design features also include dynamic pricing, room availability checks, and real-time availability updates, often using distributed caches like Redis.

Q & A

What is the primary goal of the hotel booking system discussed in the video?

The primary goal is to design a system that prevents double bookings, manages hotel reservations, and handles room availability efficiently across a large number of accommodations worldwide.

What are the key functional requirements for the hotel booking system?

The key functional requirements include hotel management (adding/removing hotels and rooms), user search and reservation capabilities (searching by filters like location and date), user notifications, and viewing past reservations.

Why is data consistency critical in the hotel booking system?

Data consistency is crucial to prevent double bookings, ensuring that no two customers can book the same room on the same day, even with concurrent requests.

What non-functional requirement is emphasized in the system design, and why is it important?

Low latency is emphasized to ensure a smooth and responsive user experience, where actions like searching for rooms and making reservations happen quickly and efficiently.

How does the system manage the availability of rooms and dynamic pricing?

The system manages room availability through the 'room inventory' table, which tracks available rooms for specific dates. Dynamic pricing is handled by the 'room pricing' table, which stores pricing information for each room type on specific dates.

Why is the use of ElasticSearch recommended for the hotel booking system?

ElasticSearch is recommended for fast, full-text search and geospatial queries, which are essential for filtering hotels and rooms based on location, price, and other criteria, significantly improving search speed.

What role do message queues like Kafka play in the system's architecture?

Message queues like Kafka help decouple the request-response cycle from heavy processing tasks, ensuring scalability, reliability, and smooth handling of asynchronous processes such as hotel additions and reservation confirmations.

How does the reservation service ensure data consistency when making a reservation?

The reservation service uses an item potency key and applies a serializable isolation level in transactions to ensure that no duplicate reservations are made and that the system maintains consistency even in a distributed environment.

What techniques are used to prevent double bookings in the hotel reservation system?

To prevent double bookings, the system uses row-level locking during database transactions, ensuring that once a reservation is made, the room availability is updated and locked to prevent further bookings.

What is the significance of using an item potency key in the reservation process?

The item potency key ensures that if the reservation request is retried, it will not result in duplicate bookings. It works by checking whether the key has been processed before, thereby avoiding repeated processing of the same request.