The Practitioner's Guide to Graph Data: Applying Graph Thinking and Graph Technologies to Solve Complex Problems

I have revised my review upward. The authors provide an environment for this, beginning on page 63. Having worked in this a while longer, I have spent many frustrating nights trying to get incompatible Python and library versions to work together. I recommend using the DataStax environment they provide rather than wasting your time setting these things up manually.

I have a fairly decent background in SQL and some NoSQL databases. Conceptually, the concept of graphs isn't too bad, but I was struggling on finding good examples of how to actually write queries and this book has saved the day.This book is really well-written, both from the perspective of theory/practical application, as well as the example Gremlin queries. I'm able to follow along using an AWS Neptune database (Tinkerpop/Gremlin-compatible) and happy to say I am now writing graph queries!Only though chapter 4 so far and very happy with the purchase.

This book is thoughtfully well done! Not only are you led through the thinking of Graph theory and solving problems with it, bu it provides a collection of examples that walk you through he stages of Graph Query examples, the thinking behind them and how to build upon your knowledge as you go through the book. If you are getting started in Graph Theory, this book will be aa great practical guide and examples to help you learn.

I thought the book was well written and easy to follow which is great since I am new to graphs. The examples were great and the explanations on why and how they work.

I'm new to using Cassandra for graph and this book does a great job explaining the concepts I needed to understand before moving to more technical content which was well-written, detailed and easy to understand. Explains advanced concepts well, too. Highly recommended.

This book has a great mix of theory and hands-on examples with through explanations. It explores several very powerful and relevant graph algorithms (exploring neighborhoods, shortest path, using trees) and really paints a good picture of what business cases are good fits for graph solutions. I highly recommend it to anyone trying to learn about the power of graph data.

Absolutely a must read book if you work with graph databases. Clearly written, real world examples, meaty topics.

too many examples of a specific graph technology. Not useful.

Few books like Odersky's "Programmign Scala", or Percivals "Architecture Patterns in Python", or Zaharia's "SPARK definitive guide" bring theory, and practice together in a language that is easy to follow, yet detailed enough to not trivialise the subject.This book is a pure delight, straight from chapter 1. As Einstein said "If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions....", this book helps us identify, and frame the problem first before delving into solutions - beautiful, and delightful.An ideal book to accompany Mark Newman's book on Networks :)

I work on Graph Databases and I found this book very helpful for both practical and more theoretical aspects. totally recommended !

Book really explained how to start graph thinking, it's more for a oltp style data gremlin.