- Introduction
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Part I — PostgreSQL Internals
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1. Storage and Memory Internals
- 1.1 Heap File Layout
- 1.2 TOAST
- 1.3 Visibility Map & Free Space Map
- 1.4 Buffer Pool
- 1.5 WAL Internals
- 1.6 Full-Page Writes
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2. Indexing Deep Dive
- 2.1 B-Tree and B+ Tree
- 2.2 Index-Only Scans and Covering Indexes
- 2.3 Hash Indexes
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1. Storage and Memory Internals
Database Engine Level Thinking
Building a mental model of PostgreSQL internals — written while learning
This book is 25% completeLast updated on 2026-09-18
Stop only using databases — start understanding them. A living study of PostgreSQL internals for backend engineers: how pages, indexes, and WAL actually work, written clearly while learning, not after mastery.
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About
About the Book
This book is for backend engineers who already ship systems people depend on — who can write SQL, know what an index is for, and have watched production surprise them anyway.
It is not a tutorial from an expert looking back. It is written alongside the learning: one mechanism at a time, rewritten carefully enough to be a lasting reference. Documentation tells you what a parameter does. This book tries to tell you what is happening underneath such that the parameter needs to exist at all.
The current edition covers PostgreSQL storage and memory (heap pages, TOAST, visibility and free-space maps, the buffer pool, WAL, full-page writes) and indexing (B-trees, leaf splits, HOT updates, index-only scans, covering indexes, and hash indexes). More chapters will follow as the study continues.
If something here is wrong or incomplete, that is expected of a living draft. Correct it, and keep going. That is the point.
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Author
About the Author
Kareem Ashraf
I’m Kareem Ashraf, a backend software engineer.
I started caring about databases for a concrete reason: I worked on a service that acted as a query builder, and the hard part was not writing SQL — it was making it fast. Indexing and vacuum helped, until they did not. I hit a ceiling where the usual knobs were not enough. To go further I had to understand the internals and the trade-offs behind them.
So I studied — books, articles, tutorials, and hands-on notes from running and breaking real systems. Database Engine-Level Thinking is that journey written down: what I have learned so far, what I am still learning, and how the internals connect to optimisation that shows up in production.
Not trivia for its own sake — mechanisms with a use case, for backend engineers who are tired of guessing.
Contents
Table of Contents
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