Leanpub Header

Skip to main content

Filters

Category: "Databases"

Books

  1. Cypher 103 with ladybugdb
    Cypher 103 with ladybugdb
    Volodymyr Pavlyshyn

    Learn graph databases the hands-on way — no servers, no setup, no fluff.Hands-On LadybugDB Cypher takes you from your first MATCH to complex recursive queries, shortest-path algorithms, and real-world AI agent graphs — all running locally in under a minute. 27 chapters. One evolving project. Every Cypher concept you need. Start querying graphs today.

  2. Rust Projects - Write a Redis Clone
    Rust Projects - Write a Redis Clone
    Explore asynchronous programming with the actor model using Rust and Tokio
    Leonardo Giordani

    Explore the power of Rust with "Rust Projects: Write a Redis Clone". This hands-on guide takes you through building a Redis-inspired database from the ground up, introducing key programming concepts like TCP connections, the RESP protocol, and concurrency. Following the CodeCrafters challenge, this book gradually builds your skills, making complex topics accessible. Whether you're new to Rust or looking to deepen your understanding, this project-based journey offers practical, real-world insights into modern systems programming. The book contains 40% discount code for CodeCrafters.io!

  3. Lift the Elephant
    Lift the Elephant
    Scaling PostgreSQL Beyond Query Optimization
    Alex Yarotsky

    When your database outgrows simple optimizations, it's time to think bigger. Lift the Elephant goes beyond query tuning to reveal actionable strategies for scaling PostgreSQL, from partitioning to high-availability architectures. Built on lessons from scaling Hubstaff, this is your playbook for navigating the challenges of database growth.

  4. Design Driven Data Engineering
    Design Driven Data Engineering
    Design-Driven Data Engineering: From Business Domain Models to Production Data Systems
    Kevin Languedoc

    Most data engineering projects fail not because of technology—but because of design.Design-Driven Data Engineering reveals a powerful new approach: start with business design, shape clarity through information modeling, and only then build systems that scale. This book gives you the frameworks, blueprints, and real-world patterns to design architectures aligned with business value, analytics needs, and modern AI-era requirements. Whether you’re an engineer, architect, analyst, or technical lead, this guide shows you how to turn complexity into clarity—and build data systems that actually work.

  5. Build a Database Server
    Build a Database Server
    Learn how real databases work by following this practical guide to building your own
    Chris Zetter

    Learn how real databases work by following this practical guide to building your own in a programming language of your choice.Build a language from scratch- Create an interpreter that can parse, type check and run SQL queries. Start with running simple queries and build up to more complex ones.Learn SQL (the fun way) - Gain a deeper understanding of SQL. Cover the order of execution of queries, how SQL uses ternary logic and the techniques that databases use to join and group data efficiently. Compare your implementation with databases such as PostgreSQL, MySQL, SQLite and DuckDB.Improve as a programmer- The perfect project to practice how to structure and refactor code as you grow the feature set of your database server. The 200+ included test cases provide a safety net for refactoring your code, giving you freedom to experiment. Learn computer science topics including creating a recursive descent parser, building a type checker and implementing iterators.

  6. Thinking in PostgreSQL
    Thinking in PostgreSQL
    A field guide to PostgreSQL for MySQL engineers
    Nick Vyzas

    Stop treating PostgreSQL like slightly broken MySQL and start using it the way it was designed.

  7. Discrete Mathematical Algorithm, and Data Structure
    Discrete Mathematical Algorithm, and Data Structure
    Major Components of Mathematics, and Computer Science Explained with the help of C, C++, PHP, Java, C#, Python, and Dart
    Sanjib Sinha

    Readers will learn discrete mathematical abstracts as well as its implementation in algorithm and data structures shown in various programming languages, such as C, C++, PHP, Java, C#, Python and Dart. This book combines two major components of Mathematics and Computer Science under one roof.

  8. Software Development Axioms, 2nd Edition
    Software Development Axioms, 2nd Edition
    Simple Rules for Higher Quality
    John "g$" Gmutza

    The software landscape is more crowed than ever! New frameworks seem to arrive weekly.  There are tons of books out there about mastering specific frameworks, but here is one to help you master the one constant factor, no matter where you are:  constructing the source code. Build great things in any programming notation; the rules are inside...

  9. Operating Petabyte-Scale ClickHouse Clusters
    Operating Petabyte-Scale ClickHouse Clusters
    A Production Engineering Guide from Architecture to Operations
    Steve Publications

    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.

  10. AI-Driven Database Query Optimization
    AI-Driven Database Query Optimization
    From Cost Models to Neural Optimizers — A Practical Engineering Guide
    Steve Publications

    What happens when AI starts making the decisions behind your database queries? This practical guide explores how modern optimizers work, then shows how machine learning and reinforcement learning can improve them. Learn to build, test and deploy AI-driven optimization systems that deliver real performance gains.

  11. The Cognos Cookbook
    The Cognos Cookbook
    Recipes for the Cognos Analytics reports that should work, but don't
    Rob Joseph

    47 Cognos Analytics report recipes, every one reproduced on a live 12.1.2 instance, with the exact error text and the fix that clears it.

  12. The RDL Cookbook
    The RDL Cookbook
    Recipes for SSRS and Power BI Paginated Reports
    Rob Joseph

    35 recipes for the SSRS and Power BI paginated report traps that waste afternoons, every one deployed and rendered on a live server first.

  13. DuckDB and the Rise of Embedded Analytical Databases
    DuckDB and the Rise of Embedded Analytical Databases
    A Comprehensive Guide to High-Performance Local Analytics
    Steve Publications

    DuckDB is changing how developers think about analytics. This practical guide takes you from its architecture and SQL capabilities to performance tuning, cloud storage and production deployments. Learn how DuckDB works, where it shines and how to build fast, flexible analytical systems around it.

  14. Reverse Engineering Databases and Storage Formats
    Reverse Engineering Databases and Storage Formats
    From Binary Bytes to Complete Understanding
    Steve Publications

    What really happens inside a database file? Learn to read binary data like a map, uncover hidden structures and turn raw bytes into a working understanding of how storage engines work. With hands-on examples from SQLite, PostgreSQL, InnoDB and more, this book shows you how to reverse engineer unfamiliar formats from the ground up.

  15. Data Management Engineering
    Data Management Engineering
    Architecture, Quality, Implementation
    Andrii Bogdanovych

    Passage 1 — Chapter 9, "Data Security": a definition that sets the technical tone immediately A hacker is someone skilled at finding undocumented techniques and loopholes in the tangled architecture of complex information systems; by intent, a "white hat" looks for such loopholes in order to strengthen the system, while a "black hat" uses them to steal or to cause harm. Passage 2 — Chapter 14, "Metadata Management": an image that explains the whole topic in one paragraph A vivid illustration: an enormous document archive with no index at all — the shelves are full, but there is no way to find out what sits on them short of examining every single box by hand. That is exactly what an organization looks like when it has piled up mountains of data without also taking care of metadata — the information physically exists, but it cannot be used systematically, since the only way to find what is needed is to already know where it sits. Knowledge about data is always scattered: in a large company, one person carries the structure of a single database in their head, another the rules of a single integration, a third the history of a single metric, and nobody holds the complete picture. Passage 3 — Chapter 15, "Data Quality Management, Part 1": why "quality" is an empty word without a yardstick A postal address missing an apartment number works perfectly well for a mass catalog mailing and works terribly for a courier who has to knock on the right door — and in both cases it is the very same row in the very same database, only the yardstick applied to it differs. Passage 4 — Chapter 21, "Organizational Change Management": the book's closing summary Data governance, the coordinating hub of eleven knowledge areas this book opened with, stays an empty frame until specific people come to value the new way of working with data through their own experience — which is exactly why a book that began by mapping the circle of disciplines around that hub fittingly closes not with another technique or tool, but with a conversation about the person without whose deliberate participation no structure ever becomes a practice.