6 New Neo4j Books Reshaping Graph Technology in 2025

Drawing from deep expertise in graph databases and Neo4j, Nexus AI presents a detailed exploration of graph theory applied to complex data relationships. You’ll gain practical skills in Cypher query language, graph algorithms, and data modeling, all supported by hands-on tutorials and numerous code examples. The book also walks you through performance tuning, helping you optimize your Neo4j implementations for real-world scenarios. For anyone aiming to deepen their technical understanding of graph databases beyond surface-level knowledge, this book offers focused, actionable insights without unnecessary jargon.

What happens when deep expertise in fraud detection meets graph data science? Timothy Eastridge draws on years of consulting with financial institutions and government agencies to show you how to harness Neo4j and Python for sophisticated data analysis. You'll learn to import and visualize complex datasets, execute Cypher queries, and even integrate cutting-edge tools like ChatGPT to enhance recommendation engines and fraud detection. Chapters like "Neo4j Vector Index and Retrieval-Augmented Generation" showcase how to blend AI with graph databases, making this a solid pick if you want to apply graph analytics to real business problems. If your focus is strictly theoretical, this hands-on guide might feel dense, but for practitioners eager to unlock actionable insights, it’s well worth your time.

This tailored book explores the latest developments in Neo4j as of 2025, offering a personalized journey through cutting-edge graph database strategies. It focuses on your interests and background to examine emerging features, innovative applications, and newly discovered techniques in Neo4j. By addressing your specific goals, the book reveals how to stay ahead in this rapidly evolving field, providing an engaging exploration of novel insights and advanced concepts. The content delves into practical aspects of the Neo4j ecosystem, including integration with AI and Python, performance enhancements, and data modeling innovations, all tailored to your learning path for maximum relevance and impact.

Unlike most Neo4j books that focus solely on syntax or basic queries, Tomaž Bratanic dives deep into graph algorithms and their practical applications in data science. You learn to build graph models from both structured and unstructured data, leveraging techniques like social network analysis, node embeddings, and link prediction. The book is especially useful if you're aiming to enhance machine learning workflows with graph data or want hands-on experience using Cypher for real projects like fraud detection or NLP-based graph construction. It’s a solid pick for data scientists ready to harness the power of connected data beyond traditional databases.

What if everything you knew about graph databases was just the surface? Kris Hermans, leveraging over 26 years in IT innovation and cyber security, offers a deep dive into Neo4j's full capabilities that goes beyond basics. You learn how to model complex relationships, master Cypher query language, and optimize performance for large-scale applications, all grounded in real-world examples like fraud detection and knowledge graphs. The book also explores Neo4j's graph data science functions and security best practices, making it a solid guide for developers and data architects seeking to harness graph technology effectively. If you're aiming to elevate your database skills with practical depth, this book fits the bill without unnecessary fluff.

What sets this book apart is its methodical Align > Refine > Design framework, which reinterprets traditional data modeling stages into a clear sequence tailored for Neo4j. Steve Hoberman, with over three decades shaping data professionals and authoring multiple data modeling texts, teams up with David Fauth to provide a hands-on guide that sharpens your schema design skills in graph databases. You’ll explore how to align business vocabulary, refine requirements, and design technical schemas, all illustrated through an animal shelter case study that brings abstract concepts to life. This approach suits technologists eager to deepen their Neo4j expertise beyond basics, offering a structured path rather than a generic overview.

This personalized AI book explores the future of Neo4j by focusing on cutting-edge developments emerging in 2025, tailored specifically to your role and interests. It examines the latest discoveries and innovations in graph database technology, offering insights into how Neo4j continues to evolve and integrate with new tools and applications. By aligning the content with your background and specific goals, the book ensures you gain relevant knowledge without wading through unrelated material. It covers emerging trends, new capabilities, and practical applications of Neo4j’s evolving ecosystem, enabling you to stay ahead in your field with a learning experience crafted just for you.

Gwendolyn Alvarado’s experience with Neo4j shines through as she guides you into the world of graph database modeling using clear, hands-on examples. You’ll explore graph theory fundamentals and how Neo4j’s Cypher query language enables building complex relationships, recommendations, and shortest path calculations. The book’s approachable scenario-based approach helps you grasp data modeling techniques specific to graph databases, accompanied by practical use cases and best practices. If you’re starting fresh with Neo4j and want to understand how to structure and query connected data effectively, this book provides a concise yet insightful foundation without overwhelming jargon or unnecessary complexity.