In this video, I'll go in detail into how the Uber app and backend really works to allow streaming millions of live locations of their drivers and riders - while making sure the app still runs fluently.

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Philipp Lackner

Uber's real-time map system evolved from inefficient polling (80% of requests) to a push-based architecture called Ramen, built on gRPC. The system uses three components: Fireball (decides when to push), API Gateway (enriches data), and Ramen server (delivers updates). To handle millions of location updates, Uber developed H3, an open-source hexagonal spatial indexing system that reduces time complexity from O(N) to O(K²) + O(M) by dividing the world into hexagons instead of calculating distances to all drivers. Edge servers minimize latency by serving users from geographically close locations, while dead reckoning and Kalman filters smooth location updates during network instability.

The Genius System Behind the Uber App’s Real-Time Map

I saw this post on YouTube and it’s really insightful. Great job man.

have seen this before on youtube still watched it again. great breakdown!

The system is really good, but it still can’t beat Grab in Vietnam