Comments about oreilly Graph Databases:

Graph Databases provides a concise introduction to this particular alternative to the relational database.

Having lots of experience with relational databases and very little experience with graph databases, I found this book to be an interesting read. The book effectively describes the weaknesses of relational databases and explains how graph databases address these weaknesses.

After introducing the idea of a graph database, the book proceeds to demonstrate domains that graph databases are suited to. This corresponds to domains where a network is a natural representation of the data, although the authors tend to suggest that graph databases are almost always more suitable than a relational database!

Next up is the demonstration of a specific implementation: Neo4J and Cypher. Examples of how to create a Neo4J database and query with Cypher follow. Explanations are a little terse, but the interested student can easily investigate further.

Finally, the book includes an interesting comparison of Graph Databases with some of the other NoSQL options available.

My only reservation is that the book felt a little unbalanced in its unwavering promotion of graph databases and the limited discussion of alternatives to Neo4J/Cypher. Overall though, this book provided a good overview of this technology and opened my eyes to the possibilities of Graph Databases.

Note: This book was provided by O'Reilly Media as part of their blogger review program.

Comments about oreilly Graph Databases:

This book significantly help in understanding what graph databases are and how to use them properly. The authors introduce basic ideas behind graph databases. They write about why the need for such databases emerged, why there's a need for having database engine in which relationships are first class citizens.

I believe that most important chapter of this book is the one that explains data modeling with graphs. The way you need to think when using graph db is totally different that in other types of db. The authors based their teachings on a set of examples, with each being discussed in detail. Various use-cases are shown, and you'll be surprised how efficient data model can be, when used properly.

You will be also able to learn basics of Cypher, which is a language that is used for querying a graph database. It's not really comprehensive introduction, so therefore it cannot be used as a reference. The book shows examples for querying Neo4j, which is probably the most popular graph database implementation. I don't think that you will be very comfortable at using Neo4j immediately after reading this book. It rather intends to make you familiar with fundamental concepts of graph databases and showing how it differs from still more popular solutions like RDBMS.

Also, some additional topics were covered, like: overview of using graph database in agile (also tdd-based) manner, introduction to Neo4j internals (different available APIs or ways of running it) or overview of other NoSQL storage.

I really liked reading it and the book made me more interested in graph-dbs as it provided solid arguments for using it in various applications. On the other hand, after reading it, I still think there's a lot for me to learn (from other resources) before I become comfortable with Neo4j. I would recommend this book to all developers, who are new to concepts of graph databases and who wants to become familiar with its strong points, before they try start using concrete graph database solutions like Neo4j