دانلود کتاب Neo4j: راهنمای قطعی دستورالعمل‌های عملی برای پیاده‌سازی گراف‌های آماده برای تولید

Graphs are everywhere you look: information is connected and doesn’t exist in isolation. Especially now, in the age of smart agentic systems, having a reliable and performant full-stack database engine that is built from the ground up to deal with richly connected information is critical to grounding your LLM’s language skills in trusted, contextual facts. Knowledge graphs are digital twins of your business that allow you to ask and answer more comprehensive questions and find the deeper insights hidden in your data. GraphRAG lets you use advanced retrieval augmented generation (RAG) patterns to make LLM output explainable and contextually grounded. My own journey with graphs started in the 1990s, when I accidentally reinvented the Dijkstra pathfinding algorithm while building client-side tooling for a multiuser dungeon online text adventure. Later, in 2008, I met Emil Eifrem, one of the founders of Neo4j, at a geek-cruise conference on the Baltic Sea. I was intrigued to hear about Neo4j for the first time, as I was working in retail applications. I wanted to know more about the applications of graph models and queries in the complex hierarchies of data. I started building open source integrations for the Neo4j database (which was back then only a small Java library, hence the “4j” name) and joined the small Swedish startup in 2010 as employee number 10. I worked on all parts of the platform, contributing to everything from the kernel to Cypher (the world’s best query language) to integration libraries for data import and application development (such as Spring Data Neo4j and GraphQL). Fifteen years later, Neo4j is one of the Swedish “unicorns,” serving thousands of large customers worldwide and offering a graph data platform that is well positioned to be a crucial part of the GenAI revolution. Coincidentally, that’s the focus of my current role as VP of Product Innovation and Developer Experience. If you’re looking for a deep dive into Neo4j by two of the best experts on the technology, you don’t have to look any further. The authors, my two amazing friends Luanne Misquitta and Christophe Willemsen, have been in the Neo4j graph space for a long time (almost as long as I have), working on open source projects as well as with a wide range of customer projects. They have been official Neo4j Ninjas for many years, answering thousands of questions, blogging, speaking, and training. We’ve shared in the Neo4j journey from both sides of the curtain: me contributing to building the database platform, and Luanne and Chris as customers, users, and contributors. Over the years I’ve worked with them a lot, in my capacity leading Developer Relations and Neo4j Labs and later Innovation and Developer Experience in Product Management, but also as a friend and mentor. I’ve always enjoyed their curiosity, smarts, and ability to take tough problems and break them down and execute on solving them in challenging production contexts. Both are graph addicts who prove that graphs are everywhere: in human interactions (good and bad), scientific research, security and dependencies in IT infrastructure, supply chains in the global economy, digital humanities, and repositories of knowledge. I encountered Luanne in 2010, when she was working in graph skills management and won our Heroku Neo4j challenge with a recipe recommendation application called Flavorwocky. Ever since then, Luanne has become an integral part of the Neo4j user community, writing articles, giving talks, and running training classes. Chris started out working on open source graph projects while building software for the Belgian Navy. When we met, I was impressed by his inquisitive nature and always deep and critical feedback. His first open source project was Neoxygen Graphgen, which generated example graph models using the power of textual graph-pattern descriptions, not for querying, but for specifying data. Later, he created and maintained the neo4j-PHP driver for many years and worked on many integrations of Neo4j with different data technologies, including Camel, Kafka, Elasticsearch, and data lakes. When Chris joined the Neo4j consultancy GraphAware as CTO and Luanne as VP of engineering, they could finally work on their passion technology full time. Not only do they work with demanding customers and projects every day, but they’ve also designed, built, and operated Hume, a comprehensive graph importation, exploration, and investigation platform with new and impressive features like complex graph analysis, virtual patterns, model mapping for massive data imports, and smart AI integrations. This book shares a lot of the tips and tricks that they’ve learned the hard way over the years. This book will get you started on your graph journey, following the team at the fictional music company ElectricHarmony as they design, develop, tune, and productionize their graph-based recommendation engine. Besides explaining the practical applications of graph modeling, querying, and importing real-world data, they also show common stumbling blocks and how to address them properly. As we follow the team through their development cycles, we learn more about the power and possibilities of graphs and about the decisions that have to be made at each stage of development. The book covers the recently released LTS version of Neo4j 5 as a robust foundation for your production deployment while also hinting at upcoming features and capabilities of the current development version. It also equips you for what’s coming: larger sharded graphs, serverless graph computation, tight integrations with large data platforms, and a graph-based AI platform.