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Graph Database Modeling: 2nd Edition
This book, "Graph Database Modeling," is born out of the necessity to equip the next generation of technologists, engineers, and data scientists with the mindset and skills required to navigate this new paradigm. It is designed to be more than just a technical manual; it is a guide to mastering the art and science of modeling the world as it truly is—a network of interconnected entities.
Key
1. NEP 2020 Aligned Focuses on conceptual understanding and practical skill development over rote learning.
2. Lucid and Simple Complex topics are broken down into easy-to-understand sections, making the book accessible to beginners.
3. Abundant Practical Uses relatable scenarios like social networks, e-commerce, and logistics to illustrate every concept.
4. Dual Model Provides in-depth coverage of both the Labeled Property Graph (LPG) model and the W3C standard RDF model.
5. Hands-On Features dedicated chapters on Cypher and SPARQL, the two most important graph query languages, with ready-to-run code.
6. Core Modeling A unique chapter dedicated to the art and science of graph data modeling, covering methodologies, patterns, and anti-patterns.
7. Advanced Topics for Includes chapters on graph algorithms, system architecture, scalability, and security to cater to advanced learners and aspiring architects.
8. Future-Forward Concludes with a look at cutting-edge topics like Graph Neural Networks (GNNs) and the role of graphs in modern AI.
Who Should Read This Book?
1. B.Tech and M.Tech students of Computer Science and IT.
2. Software Developers and Engineers looking to transition to graph technologies.
3. Data Scientists and Analysts seeking to leverage graph analytics.
4. Database Administrators and Solution Architects designing modern data platforms.
5. Faculty and educators looking for a comprehensive textbook on graph databases.
By the end of this book, you will not only understand the technicalities of graph databases but will also possess the skills and confidence to model any complex system, transforming data into insight and knowledge.
Key
1. NEP 2020 Aligned Focuses on conceptual understanding and practical skill development over rote learning.
2. Lucid and Simple Complex topics are broken down into easy-to-understand sections, making the book accessible to beginners.
3. Abundant Practical Uses relatable scenarios like social networks, e-commerce, and logistics to illustrate every concept.
4. Dual Model Provides in-depth coverage of both the Labeled Property Graph (LPG) model and the W3C standard RDF model.
5. Hands-On Features dedicated chapters on Cypher and SPARQL, the two most important graph query languages, with ready-to-run code.
6. Core Modeling A unique chapter dedicated to the art and science of graph data modeling, covering methodologies, patterns, and anti-patterns.
7. Advanced Topics for Includes chapters on graph algorithms, system architecture, scalability, and security to cater to advanced learners and aspiring architects.
8. Future-Forward Concludes with a look at cutting-edge topics like Graph Neural Networks (GNNs) and the role of graphs in modern AI.
Who Should Read This Book?
1. B.Tech and M.Tech students of Computer Science and IT.
2. Software Developers and Engineers looking to transition to graph technologies.
3. Data Scientists and Analysts seeking to leverage graph analytics.
4. Database Administrators and Solution Architects designing modern data platforms.
5. Faculty and educators looking for a comprehensive textbook on graph databases.
By the end of this book, you will not only understand the technicalities of graph databases but will also possess the skills and confidence to model any complex system, transforming data into insight and knowledge.
Audible Audio
Published July 6, 2025
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