TL;DR: The thing that caught me off guard the first time I profiled a write-heavy Postgres instance wasn't CPU saturation or memory pressure — it was await time on disk I/O. The B-tree index was healthy, the query plans looked fine, but we were hammering somewhere around 40-50k inser

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What's in this article

The Problem That Made LSM Trees Necessary

How an LSM Tree Actually Works (No Hand-Waving)

Write Amplification vs Read Amplification vs Space Amplification

Leveled Compaction vs Tiered Compaction — When Each Actually Makes Sense

LSM Trees in the Wild: RocksDB, LevelDB, Cassandra, and ClickHouse

Hands-On: Poking at RocksDB Internals

Bloom Filters: The Thing That Saves LSM Reads

Compaction Tuning: The Stuff the Docs Gloss Over

The Problem That Made LSM Trees Necessary

B-Trees Are Excellent — Right Up Until Your Write Rate Destroys You

The thing that caught me off guard the first time I profiled a write-heavy Postgres instance wasn't CPU saturation or memory pressure — it…