Learning track · Roadmap
Storage Engines & Data Modeling — Learning Track (Part 3)
Published
Your map for Part 3 of the series. Part 1 was Distributed Systems; Part 2 was Transactions & Isolation. This part goes one layer down: how a database actually stores bytes on disk and finds them fast, and how to model data.
- Mission: choose engines, indexes, and data models with judgment — grounds Parts 1 and 2 in real machinery.
- Format: structural diagrams + concrete examples. Delivered as a lean EPUB for Kindle (glossary kept in the
.md, out of the book) plus markdown source here. - Level: builds on Parts 1–2; each lesson adds senior-level depth (real-engine behaviour).
Where you are now
| Status | All 9 lessons built ✅ — read as one comprehensive page + deep-dive supplements |
| Read it | book-3-storage-engines-fundamentals.epub (send to Kindle) · or storage-engines-fundamentals.md |
| How to work it | Read in order; do each self-check from memory before peeking |
| Deep dive | lsm-compaction-deep-dive.epub — a go-deeper supplement to Lessons 3–4 (STCS vs LCS · the RUM trade-off · tombstone resurrection · L0 write stalls) |
The 9-lesson path
| # | Lesson | The single win | Status |
|---|---|---|---|
| 1 | How a Database Stores Bytes | The log + index, and the read/write tension | ✅ Built |
| 2 | B-Trees: The Default | The read-optimized workhorse | ✅ Built |
| 3 | LSM-Trees: Write-Optimized | Memtable, SSTables, compaction | ✅ Built |
| 4 | B-Tree vs LSM | The amplification trade-off | ✅ Built |
| 5 | Indexes: Finding Data Fast | Clustered vs secondary, the write cost | ✅ Built |
| 6 | Data Models | Relational, document, graph | ✅ Built |
| 7 | Schema Design | Normalization vs denormalization | ✅ Built |
| 8 | Encoding & Evolution | Forward/backward compatibility | ✅ Built |
| 9 | OLTP vs OLAP & Column Storage | Row vs column, by workload | ✅ Built |
How every lesson is built: prose → a structural diagram → a self-check → an expert corner.
Progress checklist
- Lesson 1 — How a Database Stores Bytes
- Lesson 2 — B-Trees: The Default
- Lesson 3 — LSM-Trees: Write-Optimized
- Lesson 4 — B-Tree vs LSM
- Lesson 5 — Indexes
- Lesson 6 — Data Models
- Lesson 7 — Schema Design
- Lesson 8 — Encoding & Evolution
- Lesson 9 — OLTP vs OLAP & Column Storage
Tick each box as you finish its self-check; tell me where you want to go deeper.
Files in this folder
README.md ← index + roadmap + tracker
storage-engines-fundamentals.md ← full source (includes the glossary)
book-3-storage-engines-fundamentals.epub ← lean Kindle build (glossary excluded)
diagrams/
00-cover.svg / .png ← series cover (Part 3)
01-log-hash-index.svg / .png ← Lesson 1
02-btree.svg / .png ← Lesson 2
03-lsm-tree.svg / .png ← Lesson 3
04-amplification.svg / .png ← Lesson 4
05-secondary-index.svg / .png ← Lesson 5
06-data-models.svg / .png ← Lesson 6
07-normalization.svg / .png ← Lesson 7
08-schema-evolution.svg / .png ← Lesson 8
09-row-vs-column.svg / .png ← Lesson 9Next in the series
Part 4 — Streaming & Event-Driven Architecture (Kafka, the log as source of truth, event sourcing, CQRS, stream processing, exactly-once in streams). Then Applied Systems Design.