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.

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📌 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


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