Books

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.

You don't need a graph database. You need graph thinking inside DuckDB. GraphDuck takes you from SQL adjacency lists to metagraphs, hypergraphs, and hybrid Graph RAG pipelines — all inside DuckDB. Learn to model knowledge graphs, build AI agent memory systems, run graph algorithms, and combine vector search with graph traversal in a single embedded database. Every concept comes with runnable code. No infrastructure required.

A high-performance data access layer must resonate with the underlying database system. Knowing the inner workings of a relational database and the data access frameworks in use can make the difference between a high-performance enterprise application and one that barely crawls.

Go from your first SQL query to solving real database problems with confidence. This hands-on guide covers everything from SQL fundamentals and data analysis to advanced queries, optimization and production best practices, with practical examples that work across today’s major database systems.

What really happens when PostgreSQL executes your query? Follow a SQL statement through every stage of PostgreSQL's internal pipeline—from raw text to returned results—and gain the deep understanding that transforms how you write, tune, and debug database applications.

Running ClickHouse at petabyte scale takes more than knowing SQL. This practical guide shows experienced engineers how to design, deploy and operate production clusters, from data modeling and ingestion to Kubernetes, query tuning, observability, disaster recovery and cost control, with real-world patterns and concrete configurations throughout.

Learn databases from the bottom up by coding your own, in small steps, and with simple Go code (language agnostic).Atomicity & durability. A DB is more than files!Persist data with fsync.Crash recovery.KV store based on B-tree.Disk-based data structures.Space management with a free list.Relational DB on top of KV.Learn how tables and indexes are related to B-trees.SQL-like query language; parser & interpreter.Concurrent transactions with copy-on-write data structures.

This series of test-driven small coding puzzles lets you code a database from scratch (no dependencies).We'll cover KV storage engines, LSM-Tree indexes, SQL, concurrent transactions, ACID, etc.

Master PostgreSQL administration with a practical guide to deploying, securing, optimizing, and operating production databases. Covering PostgreSQL 17 and 18, this book combines real-world examples, hands-on labs, and proven best practices for reliable, high-performance systems.

An Oracle DBA handed a MySQL database is surprised twice: first by how little seems to be there, then by how much of what you know doesn't carry over. All 79 chapters translate what you already do in Oracle — architecture, execution plans, indexing, replication, failover — into the language of MySQL 8.4, with every result measured on real servers. Continuously updated.

What really happens between typing a SQL query and getting a result? Build a database engine from the ground up in Rust and find out. You’ll work through storage, indexing, concurrency, recovery and query processing while turning each chapter’s code into one working system.

DuckDB has changed how people work with data by bringing fast analytical queries to a lightweight embedded database. Whether you are exploring Parquet files, building data pipelines or embedding analytics into your application, this handbook shows you how to get the most out of DuckDB with practical examples and real-world techniques.

A practical 62-page manual to master SQL for data analysis from scratch. Covers SELECT, JOINs, CTEs, Window Functions, and a complete RFM final project. Includes exercises, cheatsheets, and a real dataset.

STOP building fragile AI wrappers. START designing resilient AI systems. Lots of companies are trying to make their small AI experiments into big products, but they don't have a good plan. Engineers need a practical guide to build these new AI systems the right way - so they can handle scale, be reliable, and won't cost too much. This book is that guide. It explains how to design systems that use AI models. This book breaks down the architecture of real AI applications, like an AI-powered code editor or a smart learning app. It gives you a deep, practical look at the real-world challenges and solutions for building these systems. It discusses system design concepts for systems that use LLMs.

This book provides an introduction to the high-level concepts behind query engines and walks through all aspects of building a fully working SQL query engine in Kotlin.