Books

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 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.

Unlock the power of DuckDB for modern geospatial analytics. This hands-on guide helps GIS professionals master efficient spatial data management, transforming massive real-world datasets into powerful insights using SQL, Python, and DuckDB’s spatial extension. Full-color print edition is available on Amazon.

Dies ist die top-aktuelle Version 14.9 dieses Fachbuchs vom 16.10.2026 auf dem Stand Entity Framework Core 10.0.13.

Language models guess. Knowledge graphs know. Rusty Graph shows you how to build a local AI agent whose memory is a real knowledge graph — typed, validated, reasoned over, and queryable with SPARQL — all inside a single static Rust binary. No JVM. No Docker sidecar. No Python runtime bolted to the side. You will build Ares a research-assistant agent that observes papers, forms beliefs, makes promises to other agents, and tracks the provenance of every fact it holds. Chapter by chapter, Ares grows from an empty Cargo workspace into a full pipeline: > load → reason → validate → query → answer All of it in under a thousand lines of idiomatic Rust, using three crates that actually work today: `oxigraph`, `reasonable`, and `rudof_lib`. `grapfeo` You will learn how to- Model a domain as RDF triples and load them into an embedded store. - Write RDFS and OWL 2 RL axioms that infer trust, identity, and inverse relationships — automatically. - Guard your graph with SHACL shapes that reject bad data at the boundary, not in production. - Query everything with SPARQL, from simple lookups to federated queries across named graphs. - Wire the graph into a hybrid RAG pipeline so your LLM answers are grounded in facts, not vibes. Who it is forRust developers building agents, assistants, or any system where the answer "the model said so" is not good enough. You should be comfortable with Cargo and traits. You do **not** need any prior semantic-web background — every concept is introduced through Ares before any formal definition appears. Why Rust, why nowLocal agents are the next deployment target: a user's laptop, a Raspberry Pi, a WASM sandbox. Python cannot go there comfortably. Rust can. This book is the missing manual for the Rust side of the semantic web — the one that tells you exactly which crates work, where the ecosystem is thin, and how to ship anyway. Stop hoping your model tells the truth. Give it a graph that does.

Build a working SQL database engine in C++20 -- from raw pages to joins,indexes, vectorized execution and crash recovery -- one compliable, measuredchallenge at a time. Every claim is a benchmark you run yourself; every unitends with a real bug, caught and fixed. The finale holds the engine toPostgreSQL and SQLite. Complete: all 14 units. Nothing asserted.

Built for the curious, this isn’t your average programming book—it’s nearly 500 pages of hands-on mentorship beyond coding, fusing core skills in Elixir, Ecto, and SQLite with business experience and R&D tenacity. Think of it as a $500 course distilled into one powerhouse resource, with tons of learning-by-doing, in a single project. Acquire hard skills in Elixir and database modeling with Ecto's migrations, changesets, and more, re-imagining a classic database that millions around the world have used before for learning. By fearlessly ditching the "happy path", this immersive, exploratory, memorable, project-based tutorial helps you confidently tackle real-world projects with Elixir and Ecto.

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 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.

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.

Build real-world software by coding a Redis server from scratch.Network programming. The next level of programming is programming for multiple machines. Think HTTP servers, RPCs, databases, distributed systems.Data structures. Redis is the best example of applying data structures to real-world problems. Why stop at theoretical, textbook-level knowledge when you can learn from production software?Low-level C. C was, is, and will be widely used for systems programming and infrastructure software. It’s a gateway to many low-level projects.From scratch. A quote from Richard Feynman: “What I cannot create, I do not understand”. You should test your learning with real-world projects!

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.

Master performance testing and JMeter with this book written by three members of Apache JMeter's team who are also experts in the performance field.You will deeply understand how to get the most out of it, be more productive and integrate it into your Agile/DevOps processes.

Optimize Snowflake costs through design, not just configuration: from warehouse tuning to your data architecture, with practical decision criteria and SQL you can run today.

Master distributed systems through visual diagrams — from clock drift and CAP to Paxos, Raft, and distributed transactions, explained with clear illustrations instead of dense academic papers.