Part 1: Foundations

"You cannot optimize what you do not understand. You cannot understand what you have not built."

Overview

Four chapters that cover everything a database engineer needs before touching production:

#	Chapter	Core Concept	Difficulty
01	The Database Landscape	Categories, storage engines, WAL	Beginner
02	Data Modeling for Scale	Access-pattern-driven schema design	Intermediate
03	Indexing Strategies	B-tree, composite, GIN, partial indexes	Intermediate
04	Transactions & Concurrency Control	ACID, MVCC, isolation levels, locking	Advanced

Key Themes

• Storage before queries — how data lands on disk before you can query it
• Access patterns first — design your schema around how you read, not how you think
• Indexes are not free — every index costs write amplification and storage
• Isolation is a spectrum — READ COMMITTED, REPEATABLE READ, and SERIALIZABLE trade correctness for throughput

What You'll Be Able to Do

After completing Part 1 you will be able to:

• Explain why PostgreSQL uses a WAL and what happens during a crash recovery
• Design a schema for a social media application that avoids the most common N+1 query traps
• Choose between a B-tree, GIN, partial, and expression index for a given query
• Explain the difference between lost updates, phantom reads, and write skew — and which isolation level prevents each
• Implement optimistic concurrency control with a version column

Continue to Part 2

After finishing these four chapters, continue to Part 2 — Engine Deep Dives to go inside PostgreSQL and MySQL.