Uber

Answer-first: Real-time ride-hailing platforms combine HTTP/3 gRPC stream ingestion for driver GPS telemetry, Uber H3 hexagonal spatial indexing in Redis RAM, Apache Kafka/Redpanda event streaming, and DISCO global assignment matching engines to dispatch rides in under 2 seconds. Key Takeaways: Telemetry Scale: Ingest driver GPS coordinates every 4 seconds using Extended Kalman Filters and binary gRPC Protobuf streams over HTTP/3 QUIC. Spatial Pre-filtering: Index driver positions using Uber H3 Resolution 8 cells (~0.74 km²), isolating nearest candidates in <10ms. Global Matching Optimization: DISCO batched matching aggregates ride requests every 2-5 seconds, solving bipartite graph assignment problems for minimal ETA. What You’ll Learn: ...

Prerequisite: Familiarity with the concepts introduced in Part 1 — Location Ingestion. Review it first if the terminology in this part is unfamiliar. Answer-first: Uber and Grab find the nearest available driver in under 100ms by dividing the Earth’s surface into hexagonal cells (H3 index at Resolution 8, each ~0.74 km²). Instead of calculating distance to every driver, they look up only the 7 cells nearest to the rider — reducing millions of comparisons to dozens. ...

Real-Time Ride-Hailing Architecture: Matching, Spatial Indexing & Websockets The moment you open the Uber or Grab app, a cascade of real-time systems activates simultaneously: your phone begins transmitting GPS coordinates, a geospatial index updates your location, a matching engine re-evaluates nearby driver availability, a pricing model recalculates the fare based on supply-demand ratios, and a push notification pipeline prepares to deliver your match confirmation in under 3 seconds. What makes this hard is not any single component — it is the combination of all of them, processing millions of concurrent users, each with sub-second latency requirements, continuously. This post walks through all six layers of the real-time ride-hailing architecture stack, from GPS ingestion to driver notification, using Uber and Grab’s engineering practices as the reference model. ...