H3

Caching an exact GPS coordinate is impossible. Because floating-point numbers are infinitely precise, two users standing 1 meter apart will have completely different coordinates (106.0001 vs 106.0002). If your Redis key is simply lat1,lng1:lat2,lng2, your Cache Hit Rate will forever remain at 0%. Answer-first: To survive massive scale, you must implement Semantic Caching. Instead of caching raw coordinates, use Uber H3 to “snap” coordinates into 100-meter hexagonal buckets. Your cache key becomes route:{h3_origin}:{h3_dest}. This instantly transforms a compute-heavy routing problem into a lightning-fast Redis memory lookup. ...

Answer-first: How Uber and Grab handle millions of GPS pings/sec: H3 geospatial indexing, Kafka, DISCO matching engine, surge pricing, and RAMEN push notifications. 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. ...