How Uber Shows Nearby Drivers Quickly and Reliably

In this episode, we explore the system behind Uber's driver-matching functionality, capable of handling an incredible one million requests per second. We break down the key technologies that make it work, from H3, the hexagonal grid system for location indexing, to Ringpop, which scales services across servers. You'll hear about how GPS data is transformed into road segments, and how databases like Cassandra and Redis power this high-demand platform. Whether you're curious about large-scale systems or just fascinated by Uber's tech, this episode simplifies complex engineering into something anyone can understand.

Om Podcasten

"10-Minute System Design" is your go-to podcast for quick, digestible insights into system design, AI, machine learning, and distributed systems. In each episode, your hosts break down complex tech concepts into easy-to-understand discussions, it's perfect for both beginners looking to learn the basics and experienced professionals needing a quick refresh. In just 10 minutes, we dive deep into the core ideas, offering clear explanations and practical takeaways to help you stay sharp and informed in today’s fast-evolving tech landscape.