Architect a real-time Ride Matching Engine
Last updated: November 16, 2025
Quick Overview
Design a real-time ride matching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Supabase
November 16, 20258
3
1,655 solved
Design a real-time ride matching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Supabase typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
What the Interviewer Expects
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- What would the deployment pipeline look like for this system?
- How would you handle a 10x increase in traffic overnight?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
Functional Requirements
- Real-time Matching: The system must match riders with nearby drivers in real-time.
- Availability of Rides: Users should be able to view available rides and the...
Capacity Estimation
To estimate capacity, we assume:
- User Base: 10 million users with 1 million active users daily.
- Request Patterns: Each active user generates about 5 requests per hour (ride requests, statu...
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