NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence (Anglais) Broché – 8 août 2012
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Présentation de l'éditeur
The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational “NoSQL” databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program.
NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further.
The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j.
In addition, by drawing on Pramod Sadalage’s pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access.
Biographie de l'auteur
Martin Fowler, Chief Scientist at ThoughtWorks, focuses on better ways to design software systems and improve developer productivity. His books include Patterns of Enterprise Application Architecture; UML Distilled, Third Edition; Domain-Specific Languages (with Rebecca Parsons); and Refactoring: Improving the Design of Existing Code (with Kent Beck, John Brant, and William Opdyke). All are published by Addison-Wesley.
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De par les commentaires anglais, je me suis dirigé vers ce petit livre très bien écrit.
Il se décompose en 2 parties principales: une explication des concepts et un revue des différents produits
Cette première partie définit et décrit plusieurs termes / points clefs qui permettent ensuite de mieux comprendre les atouts de ces composants NoSQL ainsi que les compromis par rapport au monde SQL
La seconde partie balaie rapidement des bases comme MongoDB ou Cassandra
Au final, je suis très satisfait de ce livre, où beaucoup d'exemples sont abordés sous l'angle pratique, avec suffisamment de pseudo code pour améliorer la compréhension tout en restant concis. Sa lecture permet ensuite de mieux aborder la documentation de chaque produit / projet avec les bases pour en saisir les avantages et inconvénients. Je le recommande fortement à toutes personnes rentrant dans le domaine du NoSQL
Its not meant for developpers only. Anyone with a tech background can read.
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No more! The authors of this book present a wonderful, accessible, product-agnostic introduction to the world of NoSQL. The book first covers the four major kinds of NoSQL databases (key-value, document, column family and graph) via a highly practitioner-oriented comparative study. It then goes into various scalability issues and trade-offs, including distribution models, CAP theorem and its implications, an introduction to Map-reduce and so on. This book has demystified much of NoSQL for me and made it seem quite common-sensical.
If you are new to the Hadoop-NoSQL world, this is the book to start with before delving into any specific technology or jargon. I think that after this high-level introduction, a deep-dive using a book like 'Seven Databases in Seven Weeks' is a logical next step.
What always confused me was a comprehensive difference between these Databases and the actual concepts that underline
these databases in General.
The Authors have done a fabulous job on giving an unbiased advice on when and when not to use No SQL databases.
Regarding the contents,I am surprised by the misuse of the very common terms "relational database" and "RDBMS". Most of the time when the book refers to relational database, it actually means RDBMS (and vice versa). The book (as well as many other NoSQL advocates elsewhere) states that relational databases use ACID transactions and are not good at horizontal fragmentation (sharding) in a distributed environment. I still remember E. F. Codd's original relational database model which addresses relational data structure, entity and referential integrity constraints, and relational complete languages but says nothing about transaction processing. Transaction processing is considered a separate area from data modeling (transaction processing is explained in great details in Jim Gray's book). Also, perhaps the first book in the area, "Distributed Databases" by Ceri and Pelagatti refers to relational database almost exclusively and even uses the relational algebra select to demonstrate horizontal fragmentation. Relational RDBMSs have managed distributed databases for decades. I thought the whole database world knew this.
This book covers many topics on transaction processing and data distribution with good explanations. However, the main topics on logical data structures, integrity constraints, data manipulation and data definition languages of each "NoSQL data model" need to be addressed more clearly. Technically, transaction processing, data distributions and performance are not relevant topics on data models comparison. They are, however, relevant topics on DBMS products comparison.
Sadalage and Fowler do an excellent job in making NoSQL Distilled an "easy" read in terms of interest and flow. Their goal is not to give you an encyclopedic knowledge of every type of NoSQL implementation and product offering. Instead, they aim to give you a solid grasp of the basics, with references back to actual database implementations that use the various structures. Even after reading just the first two chapters, you should have a much clearer understanding of what makes up a NoSQL database and the various data models used to implement it. I could have stopped right there and still have been happy with the value. But it continues to deliver throughout each remaining chapter.
Part 2 of the book is where many of the "I get it" moments happened for me. As a Domino developer, I naturally read chapter 9, Document Databases, with interest. That's the structure that Domino uses (and is in fact mentioned by name in the chapter), as well as CouchDB. If you're unfamiliar with CouchDB, it was created by Damien Katz, who was also one of the chief developers at IBM working on the Domino product before leaving to start his own project. It's one of the reasons there are so many similar architectural concepts for data when you compare the two.
The authors dive into what is meant by a "document database" when it comes to NoSQL, and how it plays out in terms of how data is stored. As with the rest of the chapters, they give some examples as to how document databases differ from the traditional relational model, suitable use cases for that type of database, and most importantly, when *not* to use that type of model. Although it doesn't mention Domino specifically throughout the chapter, it's easy to take their recommendations and understand why Domino is great for some projects and absolutely the wrong choice for others.
"NoSQL Distilled" is a book that is well worth the time you'll spend reading it. Not only will you have a few "ah-ha" moments when it comes to working with and using Domino, but you'll also come away with a greater appreciation of the whole NoSQL topic and how you can use that for your own projects going forward.
Table of Contents
Part 1: Understand
Chapter 1: Why NoSQL?
Chapter 2: Aggregate Data Models
Chapter 3: More Details on Data Models
Chapter 4: Distribution Models
Chapter 5: Consistency
Chapter 6: Version Stamps
Chapter 7: Map-Reduce
Part 2: Implement
Chapter 8: Key-Value Databases
Chapter 9: Document Databases
Chapter 10: Column-Family Stores
Chapter 11: Graph Databases
Chapter 12: Schema Migrations
Chapter 13: Polyglot Persistence
Chapter 14: Beyond NoSQL
Chapter 15: Choosing Your Database