In this episode, Lucas and Luna explain why log-structured merge trees, or LSM trees, are the backbone of modern write-heavy databases like Cassandra, RocksDB, and Bigtable. They trace the problem: random writes on spinning disks were brutally slow, and even SSDs prefer sequential writes. The answer is an append-only log, a memory table, and a cascade of sorted, immutable files that occasionally merge in the background. They cover the read path—how bloom filters and sparse indexes keep lookups fast—and the compaction strategies that trade write amplification for read performance. They also unpack the real-world trade-offs: why LSM trees can lag behind on point lookups compared to B-trees, and how databases like MySQL's InnoDB chose a hybrid approach. By the end, you'll understand why your favorite database makes the storage choices it does, and you'll have a concrete example to bring to your next architecture discussion. Tune in for a clear, practical breakdown of one of the most important data structures in modern storage.