You know that little message—“This username is already taken”? Behind that simple UX lies a crazy mix of advanced data structures and distributed systems. In this video, we explore how tech giants like Google, Meta, and Amazon check billions of usernames with near-instant accuracy. You’ll discover how Redis hashmaps provide lightning-fast lookups, why Tries and B+ Trees are ideal for autocomplete and ordered search, and how Bloom filters act as the first line of defense against unnecessary database hits. From load balancing across data centers to querying distributed databases like Cassandra or Spanner, this video breaks down how username checks are made fast, scalable, and reliable—at a truly global level. Diagram Tools: 📌 Timestamps 00:00 Introduction – Why Username Checks Are Harder Than You Think 00:55 Redis Hashmaps – Fast Lookups in Memory 02:05 Trie Structures – Prefix Matching & Autocomplete 03:36 B+ Trees – Ordered Lookups in Massive Datasets 05:32 Bloom Filters – Lightning-Fast Probabilistic Checks 08:02 Load Balancing & Multi-Layer Lookup Architecture AWS Certification: AWS Certified Cloud Practioner: AWS Certified Solution Architect Associate: AWS Certified Solution Architect Professional: #redisdatabase #systemdesign #distributedsystems #bloomfilters