Book
Database Internals
Alex Petrov
Summary
B-Tree と LSM-Tree のストレージエンジン実装から、Raft / Paxos などの分散合意アルゴリズムまで、 現代データベースエンジンの「内部」を詳解。ベンダーのマーケティング用語に惑わされず、 アーキテクチャの本質と制約を見抜くための強靭なメンタルモデルを養う。
Target Readers
- DB 内部実装を本質から理解したい上級エンジニア
- 分散データベースのアーキテクチャ判断を下したいアーキテクト
Tags
Colophon
- Publisher
- オライリー・ジャパン
- ISBN
- 978-4873119540
- Published
- Jul 2021
- List price
- ¥4,180incl. taxMay differ from the actual selling price on Amazon
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Prerequisites
- Recommended
SQLパフォーマンス詳解
Markus Winand
Reason: After understanding the internals of B-Tree indexes in 'SQL Performance Explained', broaden your view with Alex Petrov's 'Database Internals' to the LSM-Trees and various storage engines beyond the B-Tree. Comparing data structures with different read/write characteristics cultivates judgment for choosing a database engine.
- Recommended
PostgreSQL徹底入門 第4版
近藤雄太, 正野裕大, 坂井潔, 鳥越淳, 笠原辰仁, 石井達夫
Reason: Once you understand one concrete RDBMS implementation (PostgreSQL), you want a map to put it in perspective. Petrov's 'Database Internals' systematizes storage engines and distributed implementations across products, letting you grasp where 'this PostgreSQL mechanism' sits in the general picture.
Sources
- Related
プログラマのためのSQL 第4版
Joe Celko
Reason: Pushing Celko's set-theoretic advanced SQL to its limits sparks interest in how those declarative queries are executed and stored internally. Learning storage engines and index implementations in Petrov's 'Database Internals' bridges the gap between SQL's declarations and their physical execution.
Sources
Next Books
- Prerequisite
Designing Data-Intensive Applications
Martin Kleppmann
Reason: Only after understanding single-node storage-engine internals do discussions of consistency, replication, and partitioning across multiple nodes become grounded. Kleppmann's 'Designing Data-Intensive Applications' is the capstone that systematizes the principles of distributed data systems, placing internals knowledge as a required prerequisite.
- Recommended
Database Reliability Engineering
Laine Campbell, Charity Majors
Reason: Understanding the internals of storage engines and replication lets you predict, from structure, what to monitor and what can break in production. 'Database Reliability Engineering' bridges that internal knowledge into operational design—capacity planning, incident response, data integrity.