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Graph Databases [Anglais] [Broché]

Ian Robinson , Jim Webber , Emil Eifrem

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Descriptions du produit

Graph Databases Discover how graph databases can help you manage and query highly connected data. With this practical book, you'll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Full description

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Amazon.com: 3.7 étoiles sur 5  14 commentaires
17 internautes sur 17 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 decent 3.7 23 août 2013
Par Vivace - Publié sur Amazon.com
Format:Broché|Achat vérifié
The good:
- gives you concrete, real motivation for using graphDB
- decent discussion of modeling real world problems as graphs
- nice coverage of cypher
- nice coverage of neo4j

the bad:
- reads a bit like an advertisement for neo4j
- doesnt discuss much about pregel or other distributed graph systems.
- the last chapter is entitled 'predictive analytics' was a bit of a let down. The first half is just BFS, DFS and A* and the second half discusses `triadic closure' ...
- its a short book and a bit fluffy.

on the whole:
i was very excited to get this book, had it on preorder....its not the bombshell i was hoping for but it is a great step in the right direction.
10 internautes sur 10 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 New approach to data modelling explained in detail 23 juin 2013
Par Krzysztof Ropiak - Publié sur Amazon.com
Format:Broché
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.
4 internautes sur 4 ont trouvé ce commentaire utile 
1.0 étoiles sur 5 Should be named Neo4J Database 16 mars 2014
Par Rafael - Publié sur Amazon.com
Format:Format Kindle|Achat vérifié
The book gives an introduction in the concepts of Graph Databases. But later on is just about Neo4j, sure it is a very nice graph database but not the only one. I've got extremely disappointed with this title because I was expecting a thorough elaboration of graph databases to help me decide which would I use in my project, instead I get just a Neo4J user's guide, something you can easily find on the Internet. For this waste of money I rate it with just 1 star.
3 internautes sur 3 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 None of the book examples works :/ 31 octobre 2013
Par Gravity - Publié sur Amazon.com
Format:Format Kindle
I'm a complete noob to graph databases, when I tried to run the examples from page 44 onwards, none works, so they just paste a query on the book without test beforehand?. Apparently the query provided is referencing a non-existent index, but the funny thing is that indexes build process is not explained before run the queries, I spent hours looking on search engines for a definitive solution, what a waste of time.
1 internautes sur 1 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Solid introduction to Graph Databases 25 août 2013
Par Devendra - Publié sur Amazon.com
Format:Broché
This books lays a solid foundation for understanding what Graph Databases are all about. Implementation details are all based on Neo4J, except for a fleeting reference to Twitter's FlockDB when discussing scalability.

Chapters 1 and 2 provide overview of Graph Databases, and compare them to Relational and NoSQL Databases. Appendix A provides useful overview of different NoSQL databases.

Data modeling with Graph Databases is compared to relational databases in Chapter 3. The creation of a domain model is demonstrated using Systems Management Domain. Cross-domain modeling is also demonstrated. The models are created and queried using Cypher. Common modeling pitfalls are also discussed.

Chapter 4 discusses data modeling in more detail. Nodes are used to represent things, facts, and complex value types. Relationships are used to establish connections and semantics. Nodes and relationships have properties. Versioning of data is done inside the graph model, the downside being query complexity. Neo4J can be embedded into applications or deployed in server mode, benefits of each mode are discussed. Server mode allows for extensions written using JAX-RS, named indexes can be created using the REST API. High availability can be achieved using clustering and load balancing. Object caching provides the best querying performance. Redundancy and load requirements can be used to determine number of machines. Test-driven data model development can be done with ImpermanentGraphDatabase Java class, it also allows creation of named indexes.

Chapter 5 provides common real-world use cases and examples. Domains covered in detail include social network, authorization and access control, and logistics.

Chapter 6 discusses native graph processing and storage. Index-free adjacency provides better query performance. Programmatic access to Neo4J database is provided by the Kernel, Core and Traverser APIs. Non-functional characteristics such as transactions (ACID properties), recoverability, availability, scale (capacity, latency, and throughput) are also discussed.

Graph algorithms such as depth- and breath-first search, Dijkstra's algorithm, and A* algorithm are detailed, in chapter 7. Analyses based on these algorithms, and techniques from graph theory and social sciences, can be used to gain new insights from a domain. Social graph properties such as Triadic Closures, Structural Balance, and Local Bridges can be used to gain new insights into a social network.

I found the book extremely useful to understand what Graph Databases are all about. [Disclaimer] I thank O'Reilly Media for providing a review copy.
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