Modern databases are built on a foundation of storage design, query execution, concurrency control, indexing, memory management, and distributed systems engineering. Database Engineering with Rust is a practical technical guide to understanding how database systems work from the inside out, using Rust as the implementation language for building reliable, efficient, and maintainable data infrastructure.

This book guides readers through the core components of database engineering, including storage engines, write-ahead logging, indexing structures, query parsing, execution models, transaction handling, caching, compaction, and system-level performance considerations. Rather than treating databases as black boxes, it breaks down the architectural decisions that shape how data is stored, retrieved, processed, and protected.

Readers will explore how Rust's ownership model, type system, memory safety guarantees, and concurrency tools can be applied to the design of database internals and backend infrastructure. The focus is on clear engineering principles, practical system design, and implementation patterns that help developers reason about correctness, reliability, and performance in data-intensive software.

Inside, readers will learn how to:

Design the core architecture of a storage engine

Understand log-structured and page-oriented storage models

Implement indexing strategies for efficient data retrieval

Build query parsing and execution components

Reason about transactions, durability, and consistency

Use Rust for memory-safe systems programming

Structure database infrastructure for maintainability and reliability

Analyze trade-offs in performance, concurrency, and fault tolerance

Database Engineering with Rust is written for software engineers, Rust developers, backend programmers, infrastructure engineers, and technically advanced readers who want to understand how modern database systems are designed and implemented. It provides a grounded path from database concepts to systems-level implementation, making it a valuable resource for anyone building data platforms, storage systems, query engines, or high-performance backend services.