Design a Rental Marketplace Backend
Quick Overview
This question evaluates a candidate's ability to design a scalable, low-latency backend for a global vacation-rental marketplace, testing competencies in data modeling, search and geo-indexing, availability and booking consistency, storage, caching, partitioning and replication, failure handling, and machine learning integration for recommendations and ranking. It is commonly asked to assess architectural reasoning, trade-off analysis, capacity planning, and operational resilience for distributed systems; the category is System Design (backend engineering) and the level of abstraction is practical application focusing on high-level architecture and component interactions rather than implementation details.
Design the backend for a large vacation-rental marketplace similar to Airbnb.
The system should support:
- A home page that shows popular destinations and personalized listing recommendations.
- Search across millions of listings by location, travel dates, guest count, price range, and amenities.
- Accurate availability checks and booking creation.
- High traffic, low-latency reads, and global scale.
Discuss:
- Core APIs and data models for listings, calendars, bookings, users, and recommendations.
- How search indexing works, including geo search, filtering, ranking, and pagination.
- How to keep availability fresh in search results while preventing double-booking under concurrent requests.
- Storage choices, caching, partitioning, replication, and failure handling.
- How machine learning can be integrated into the home page and search ranking without making the system unavailable if ML services fail.