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Design a ride-hailing platform like Uber

UberSoftware Engineer · Onsite
HardSoftware EngineerOnsiteSystem Design

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This question evaluates a candidate's competency in large-scale system design, covering distributed systems architecture, data modeling, real-time location streaming, matching algorithms, scalability, fault tolerance, and secure payment handling.

You are asked to design a large-scale ride-hailing platform similar to Uber.

Requirements

Functional requirements

  • Riders can:
  • Sign up, log in, and manage their profile.
  • Request a ride from a pickup location to a destination.
  • See nearby available drivers and estimated time of arrival (ETA).
  • See an estimated fare before confirming the ride.
  • Track the driver in real time once a ride is accepted.
  • Pay via stored payment methods (e.g., credit card).
  • Rate and review drivers after the ride.
  • Drivers can:
  • Sign up, go through onboarding, and register their vehicle.
  • Go online/offline to indicate availability.
  • Receive ride requests and accept/decline them.
  • Navigate to the rider and then to the destination.
  • The system should:
  • Automatically match riders with nearby available drivers.
  • Support surge pricing based on demand and supply in a geographic area.
  • Store trip history (routes, prices, timestamps) for both riders and drivers.
  • Send real-time notifications (push/SMS) about ride status updates.

Non-functional requirements

  • High availability: Service should remain usable even if individual components fail.
  • Low latency:
  • Rider should see ETA and match results quickly (e.g., within a few hundred ms).
  • Location updates should appear near real time.
  • Scalability:
  • Support millions of daily active users in multiple cities/regions.
  • Reliability and consistency:
  • Payments and trip records must not be lost or double charged.
  • Some data (e.g., live location) can be eventually consistent.
  • Security and privacy:
  • Protect user data and payment information.

Task

Design the backend system for this platform. In your answer, cover:

  1. High-level architecture:
  • Main services/components and how they interact (e.g., client apps, API gateway, core services).
  1. Data model and storage:
  • Key entities (users, drivers, vehicles, trips, locations, payments) and a rough schema.
  • Choice of databases (SQL / NoSQL / in-memory) and what to store where.
  1. Ride request and matching flow:
  • How a rider request flows through the system.
  • How to find and choose a nearby driver efficiently.
  1. Real-time location tracking:
  • How drivers send location updates.
  • How the system stores/serves this for ETAs and maps.
  1. Scalability and partitioning:
  • How to scale by city/region or other keys.
  • How to handle hotspots during rush hour.
  1. Reliability and fault tolerance:
  • How to handle failures of individual services or data centers.
  • How to ensure payments and trip records are durable.
  1. Additional considerations (briefly):
  • Surge pricing approach.
  • Monitoring, logging, and key metrics you would track.