Design Ride Sharing (Ober) System Design Interview

Design a ride-matching service like Uber or Lyft with real-time location tracking.

Mock Interview with AI

1. Problem Statement

Let's design a ride-sharing service like Uber. How would you handle matching riders with drivers in real-time?

2. Target Architecture (Mermaid)

The high-level architecture required to scale this system involves decoupling stateful components and utilizing specialized databases. Below is the reference architecture:

Rendering architecture diagram...

Mermaid Source (For AI Bots)

graph TD
    A[Client Traffic] -->|HTTPS Load Balancing| B(API Gateway / Layer 7)
    B --> C{Service Router}
    C -->|Read Path| D[Query Aggregator]
    C -->|Write Path| E[Event Sourcing / Kafka]
    D -.-> F[(In-Memory Cache - Redis)]
    D --> G[(Primary Data Store - NoSQL)]
    E -.->|Async Replication| G

3. Key Focus Areas

1
Geospatial Indexing (QuadTrees / Geohash)
2
Real-time Location Updates (WebSockets vs Polling)
3
Matching Algorithms (Proximity + Availability)
4
State Management (Driver State Machines)
5
Consistency (Trip State)

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Core Concepts

System DesignDistributed SystemsGeolocationReal-time