Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement

Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement
by Eric Redmond and Jim R. Wilson
354 pages
Published: 2012-05-11
Release: P2.0 (2013-01-28)
ISBN: 978-1-93435-692-0

About this Book

Redis, Neo4J, CouchDB, MongoDB, HBase, Riak, and Postgres: with each database, you’ll tackle a real-world data problem that highlights the concepts and features that make it shine. You’ll explore the five data models employed by these databases: relational, key/value, columnar, document, and graph. See which kinds of problems are best suited to each, and when to use them.

You’ll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon’s Elastic Compute Cloud (EC2).

Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that’s more than the sum of its parts, or find one that meets all your needs at once.

Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.

What You Need:

You’ll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

About the Author

Eric Redmond has been in the software industry for more than 15 years, working with Fortune 500 companies, governments, and many startups. He is a coder, illustrator, international speaker, and active organizer of several technology groups.

Jim R. Wilson started hacking at the age of 13 and never looked back. He began tinkering with NoSQL databases in 2007 and has contributed code to large-scale open source projects such as MediaWiki and HBase.


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