Data is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available – from a traditional relational database to newer No SQL approaches – and make informed decisions about challenging data storage problems. This is the only comprehensive guide to the world of No SQL databases, with in-depth practical and conceptual introductions to seven different technologies: Redis, Neo4J, Couch DB, Mongo DB, HBase, Postgres, and Dynamo DB. This second edition includes a new chapter on Dynamo DB and updated content for each chapter.
While relational databases such as My SQL remain as relevant as ever, the alternative, No SQL paradigm has opened up new horizons in performance and scalability and changed the way we approach data-centric problems. This book presents the essential concepts behind each database alongside hands-on examples that make each technology come alive.
With each database, tackle a real-world problem that highlights the concepts and features that make it shine. Along the way, explore five database models – relational, key/value, columnar, document, and graph – from the perspective of challenges faced by real applications. Learn how Mongo DB and Couch DB are strikingly different, make your applications faster with Redis and more connected with Neo4J, build a cluster of HBase servers using cloud services such as Amazon’s Elastic Map Reduce, and more. This new edition brings a brand new chapter on Dynamo DB, updated code samples and exercises, and a more up-to-date account of each database’s feature set.
Whether you’re a programmer building the next big thing, a data scientist seeking solutions to thorny problems, or a technology enthusiast venturing into new territory, you will find something to inspire you in this book.
What You Need:
You’ll need a *nix shell (Mac OS or Linux preferred, Windows users will need Cygwin), Java 6 (or greater), and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.Over de auteur
Jim R. Wilson is a software engineer at Google creating data visualizations on the Big Picture team. He’s contributed to Tensor Flow’s visualization suite, Tensor Board, and other open source projects.