Databases

Your ORM works until it doesn't: a query returns ten thousand duplicated rows, a migration refuses a partitioned table, or the feature the product needs is one PostgreSQL has had for years. Twenty-one chapters that close the gap — LINQ translation, query plans, JSONB, full-text search, PostGIS and pgvector, then auditing, multi-tenancy and deployment. Every listing run against a live database. Every output captured, never typed.

Metagraphs for Agentic AI: Beyond Triples, Beyond HypergraphsFrom Knowledge Graphs to Knowledge ArchitecturesThe triple is not enough.Every AI engineer building agent memory hits the same wall. You model a meeting as a knowledge graph triple — and immediately lose the fact that five people were in the room, a decision was made, and that decision caused three downstream actions. You reify. You flatten. You create workarounds. And your "knowledge graph" becomes a tangle of auxiliary nodes that machines can traverse but no human can reason about.This book shows you the way out. What You'll Learn Metagraphs are graph structures where edges connect sets of nodes to sets of nodes — and where edges themselves can be referenced as first-class nodes. They are the missing data structure for AI agents that need to remember, reason, and coordinate like humans do.This book takes you on a complete journey:Hypergraphs first. You'll learn what they are, why they matter, and where they break down. You'll implement them three ways — in SQL, in LadybugDB (Cypher), and in TypeDB — so you understand the tradeoffs viscerally, not just theoretically.Then metagraphs. You'll see how metagraphs solve the fundamental hypergraph problem (edges that can't be nodes), explore RDF named graphs as a lightweight metagraph, and implement full metagraphs in the same three database paradigms with production-ready, commented code.Then the big ideas. Semantic Spacetime. Holonic systems. Human cognitive architecture mapped to graph structures. Multi-agent coordination. Promise Theory for autonomous AI networks. This is where metagraphs stop being a data structure and become an architecture for intelligence. Who This Book Is For You're a software engineer, AI researcher, or knowledge graph practitioner who builds real systems. You've used Neo4j or RDF stores. You've built RAG pipelines. You've felt the limits. You want to know what comes next.No PhD required. Every concept comes with working code in SQL, Cypher, TypeQL, SPARQL, and Python. What Makes This Book Different This isn't a theoretical monograph. It's the distillation of two and a half years of research, 130+ published articles, and hands-on implementation at the intersection of knowledge graphs and agentic AI.Every chapter bridges theory and practice. You'll read about Basu and Blanning's formal metagraph definition — and then build the schema in PostgreSQL. You'll learn Mark Burgess's Promise Theory — and then model a multi-agent coordination protocol as a six-layer promise graph. You'll understand why labeled property graphs are secretly metagraphs — and what that means for your Neo4j deployment today. 18 Chapters. Three Parts. One Argument. Part I — The Hypergraph Foundation (7 chapters): From the knowledge representation crisis through hypergraph theory to three complete database implementations.Part II — The Metagraph Solution (5 chapters): Metagraphs as the answer, RDF named graphs as a bridge, and three full metagraph implementations with detailed commentary.Part III — Theory Meets Practice (6 chapters): Semantic Spacetime, labeled property graphs, AI memory and human cognition, holonic systems, agent-to-agent interaction, and Promise Graphs for network-of-networks coordination. The Core Thesis If you want AI agents that reason like humans, you need knowledge structures that capture how humans actually organize knowledge — not as flat collections of facts, but as nested, hierarchical, context-rich, temporally-aware structures where relationships themselves carry meaning and can be the subject of further reasoning.Metagraphs are that structure. This book shows you why, and how to build with them.

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 book offers practical guidance on managing data as a product, drawing from real-world experience to empower you to implement your own data product-centric approach.

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.

Master the art of performance testing and regression detection in Business Central! This comprehensive guide unlocks the secrets of the Performance Toolkit (BCPT)—from writing custom test scenarios to detecting performance regressions across versions. Learn how to simulate hundreds of concurrent users, analyze telemetry with Power BI, and integrate performance testing into your CI/CD pipelines. Whether you're preparing for MB-820 certification or ensuring your extensions can scale to production loads, this is your roadmap from manual testing to automated performance validation.

Stop being a syntax typist. Master Clean Code Architecture and Algorithmic Thinking to become a professional Software Architect in 2026. This blueprint teaches you to build Scalable Systems using Binary Logic, Big O Notation, and proven Software Engineering Patterns. Perfect for the modern Backend Developer, self-taught coder, and Tech Entrepreneur looking to design high-performance software from scratch.

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.

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.

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.

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!

This expanded chapter, from Phaser Game Starter Kit Collection, leads you through "White Labeled" Role-Playing "Content-as-a-Service" - an innovative approach in "Headless HTML5 Game Design". It provides both front- & back-end encoding. These advanced topics of "full-stack" development is for anyone interested in RPG "trade-secrets" development.

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.

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.

Modelación de base de datos relacional.Normalización y documentación de base de datos.Programación DDL en MySQL, Oracle y SQL Server.