Uber Redis Interview Questions 2026
Published July 22, 2026 · Updated July 22, 2026
5 real Redis interview questions asked at Uber. Upvoted by engineers who cleared the loop. Covers System Design, Technical rounds.
5 questions
258 engineers asked
309 upvotes
Company: Uber
Technology: Redis
All Redis Questions Asked at Uber
Uber
Hard
System Design round
Distributed SystemsRedisKafka
Design Uber's driver-rider matching system.
How do you match the nearest available driver to a rider within 200ms at global scale?
Cover: geospatial indexing (H3/S2), the dispatch algorithm, how you handle supply-demand imbalances, and what happens when a matched driver rejects the trip.
↑ 99 upvotes · 98 engineers asked this · SDE2
Uber
Hard
System Design round
KafkaRedisDistributed Systems
Design Uber's dynamic pricing (surge) system.
When supply is low and demand is high in a geofenced zone, prices increase automatically.
Explain the data pipeline, the pricing model, how you prevent oscillations (price going up → drivers rush in → price drops → drivers leave), and regulatory constraints.
↑ 75 upvotes · 74 engineers asked this · SDE2
Uber
Hard
System Design round
Distributed SystemsRedisKafka
Design Uber Eats' order batching system. A single delivery partner picks up orders from multiple nearby restaurants and delivers to multiple customers in one trip. How do you optimise the route and assignment?
↑ 62 upvotes · 41 engineers asked this · SDE2
Uber
Hard
Technical round
Distributed SystemsRedis
Uber uses H3 hexagonal geospatial indexing. Explain why hexagons are better than squares or lat/lng grids for proximity searches. How do you find all drivers within 2km of a rider using H3 resolution levels?
↑ 54 upvotes · 34 engineers asked this · SDE2
Uber
Medium
Technical round
2-5 yearsRedis
You need to track the top 10 most active drivers by trip count, updated in real time. Which Redis data structure fits this, and why not just a plain hash with manual sorting?
↑ 19 upvotes · 11 engineers asked this · SDE2
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Frequently asked questions
Design Uber's driver-rider matching system.
Design Uber's driver-rider matching system.
How do you match the nearest available driver to a rider within 200ms at global scale?
Cover: geospatial indexing (H3/S2), the dispatch algorithm, how you handle supply-demand imbalances, and what happens when a matched driver rejects the trip.
Design Uber's dynamic pricing (surge) system.
Design Uber's dynamic pricing (surge) system.
When supply is low and demand is high in a geofenced zone, prices increase automatically.
Explain the data pipeline, the pricing model, how you prevent oscillations (price going up → drivers rush in → price drops → drivers leave), and regulatory constraints.
Design Uber Eats' order batching system. A single delivery partner picks up orders from multiple nearby restaurants and delivers to multiple customers in one trip. How do you optimise the route and assignment?
Design Uber Eats' order batching system. A single delivery partner picks up orders from multiple nearby restaurants and delivers to multiple customers in one trip. How do you optimise the route and assignment?
Uber uses H3 hexagonal geospatial indexing. Explain why hexagons are better than squares or lat/lng grids for proximity searches. How do you find all drivers within 2km of a rider using H3 resolution levels?
Uber uses H3 hexagonal geospatial indexing. Explain why hexagons are better than squares or lat/lng grids for proximity searches. How do you find all drivers within 2km of a rider using H3 resolution levels?
You need to track the top 10 most active drivers by trip count, updated in real time. Which Redis data structure fits this, and why not just a plain hash with manual sorting?
You need to track the top 10 most active drivers by trip count, updated in real time. Which Redis data structure fits this, and why not just a plain hash with manual sorting?