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Building Database Engines from Scratch

A Hands-On Guide to Storage, Concurrency, Query Processing, and Reliability in Systems Programming

Building Database Engines from Scratch
This book is 100% completeLast updated on 2026-10-01
Steve Publications

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.

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About the Book

This book teaches you how modern database systems work by having you build one. Over fifteen chapters we will design and implement a complete relational database engine in Rust: storage layers that read and write pages to disk, a buffer pool manager that caches hot data in memory, write-ahead logging for crash recovery, B-tree indexes for fast lookups, a transaction system with proper isolation and concurrency control, a SQL parser, a cost-based query optimizer, and an execution engine that runs joins, sorts, and aggregations. Every chapter adds working code to the same project so that by the end you have a coherent, functional database application rather than a collection of isolated examples. If you are a software engineer who wants to understand what happens between typing SELECT * FROM users and seeing results on screen, this is the book for you.

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DatabasesRustAlgorithmData StructuresComputers and Programming

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About the Author

Steve Publications

Steve is a technology professional with over 20 years of experience in software development, server infrastructure, cybersecurity, vulnerability research and reverse engineering. He specializes in analyzing complex systems, identifying weaknesses and improving security.

Beyond his professional work, Steve collaborates with researchers and industry experts to create practical technical books covering software development, cybersecurity, cloud computing, DevOps, AI and enterprise technologies. His goal is to help IT professionals, students and enthusiasts develop practical skills through clear explanations, real-world examples and hands-on exercises.

At Steve Publications, we use AI to assist with translation, proofreading and editing but not to replace the research, technical expertise or hands-on experience behind our books. Some authors publish under pseudonyms for privacy or professional reasons.

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Contents

Table of Contents

A Hands-On Guide to Storage, Concurrency, Query Processing and Reliability in Systems Programming

Chapter 1: Why Build a Database?

  1. The Hidden Complexity of Every Database Query
  2. What You Will Build and Why It Matters
  3. A Tour of the Architecture We Are Going to Construct
  4. Implementation Roadmap: From Empty Project to Working Database
  5. How to Read This Book and Use the Code

Chapter 2: Project Setup and Systems Foundations

  1. Choosing Rust for Database Implementation
  2. Project Structure and Build Configuration
  3. Core Abstractions: Pages, Records and Offsets
  4. Error Handling Strategy Across the Engine
  5. First Binary: Initializing an Empty Database File

Chapter 3: Storage Fundamentals - Disks, SSDs and Pages

  1. How Disks and SSDs Actually Work
  2. Why Databases Think in Pages, Not Bytes
  3. Building Our Page Abstraction Layer
  4. Binary Data Layout: Endianness, Alignment and Serialization
  5. Implementing the Storage Manager Interface

Chapter 4: File Format and Slotted Page Records

  1. Designing the Database File Format
  2. Slotted Page Layout: Headers, Directories and Records
  3. Variable-Length Record Serialization
  4. Free-Space Management Within Pages
  5. Implementing Page Reads and Writes with Verification

Chapter 5: Buffer Pool Manager - Caching at Scale

  1. The Purpose of Buffer Pools and Why They Are Hard
  2. Pinning Semantics and Reference Counting
  3. Dirty Pages, Write Policies and Flush Behavior
  4. Handling Memory Pressure and Eviction Under Load

Chapter 6: Logging, Durability and Crash Recovery

  1. The Durability Problem and Why fsync Matters
  2. Write-Ahead Logging: Protocol and Invariants
  3. Designing Our Log Record Format
  4. Checkpointing Strategies and Implementation
  5. Crash Recovery: Redo and Undo in Practice

Chapter 7: Indexing - B-Trees, Hash Indexes and Beyond

  1. Why Indexes Exist and What They Trade Away
  2. Implementing a B+ Tree from Scratch
  3. Page Splits, Merges and Concurrency Considerations
  4. Hash Indexes for Equality Lookups
  5. LSM Trees and Alternative Index Architectures

Chapter 8: Transactions and Concurrency Control

  1. ACID Properties: What They Mean in Implementation Terms
  2. Locking Protocols and Two-Phase Locking
  3. Deadlock Detection and Prevention
  4. Latches vs Locks: Protecting Data Structures
  5. Implementing MVCC with Snapshot Isolation

Chapter 9: SQL Parsing and Semantic Analysis

  1. Designing Our SQL Subset and Grammar
  2. Lexical Analysis: Tokenizing SQL Input
  3. Recursive Descent Parsing and AST Construction
  4. Symbol Tables and Schema Resolution

Chapter 10: Query Planning and Cost-Based Optimization

  1. From AST to Logical Plan
  2. Physical Operators and Execution Strategies
  3. Building a Cost Model from Statistics
  4. Cardinality Estimation: Histograms and Selectivity
  5. Join Ordering and Query Rewrite Rules

Chapter 11: Query Execution Engine

  1. Operator Architecture: Iterators and Pipelining
  2. Table Scans and Index Scans
  3. Filtering, Projection and Expression Evaluation
  4. Join Implementations: Nested-Loop, Hash and Merge
  5. Aggregation and Grouping with Hash Tables

Chapter 12: Performance Engineering and Optimization

  1. Understanding Database Performance Characteristics
  2. I/O Patterns: Sequential Versus Random Access
  3. Cache Efficiency and Data Locality
  4. Vectorized Execution vs Tuple-at-a-Time Processing
  5. Profiling, Benchmarking and Workload Generation
  6. Systematic Optimization: Finding and Fixing Bottlenecks

Chapter 13: Reliability, Correctness and Failure Handling

  1. Crash Consistency: Guarantees and Invariants
  2. Torn Pages and Partial Writes
  3. Corruption Detection with Checksums and Validation
  4. Disk-Full Conditions and Safe Failure Modes
  5. Backup, Restore and Integrity Verification

Chapter 14: Beyond Single Node - Distributed Database Concepts

  1. Why Single-Node Databases Eventually Hit Limits
  2. Replication Architectures: Leader-Follower and Multi-Leader
  3. Log Replication and Consistency Models
  4. Sharding and Distributed Query Execution
  5. Consensus, Fault Tolerance and Rebalancing

Chapter 15: Conclusion - From Educational Engine to Production System

  1. Architecture Review: How All Subsystems Fit Together
  2. What We Simplified and Why Production Systems Differ
  3. Comparing Our Implementation to Real Databases
  4. Paths Forward: Extending Your Database Engine
  5. The Engineer’s Mindset for Building Reliable Systems

References

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