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Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence (Microsoft patterns & practices)

ISBN: 9781621140306
Publisher: Microsoft patterns & practices
Edition: 1
Publication Date: 2013-09-27
Number of pages: 274
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  • Regular price $66.24

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All applications use data, and most applications also need to store this data somewhere. In the world of business solutions, this often meant creating a relational database. However, relational technology is not always the best solution to meet the increasingly complex data-processing requirements of modern business systems, especially when this processing involves storing and retrieving massive amounts of data.

The advent of NoSQL databases has changed the way in which organizations have started to think about the way in which they structure their data. There is no standard definition of what a NoSQL database is other than they are all non-relational. They are less generalized than relational databases, but the driving force behind most NoSQL databases is focused efficiency and high scalability.

The downside of NoSQL is that no single database is likely to be able to support the complete range of business requirements mandated by your applications. How do you select the most appropriate database to use, or should you remain with the relational model? A modern business application is not restricted to using a single data store, and an increasing number of solutions are now based on a polyglot architecture. The key to designing a successful application is to understand which databases best meet the needs of the various parts of the system, and how to combine these databases into a single, seamless solution.

This guide helps you understand these challenges and enables you to apply the principles of NoSQL databases and polyglot solutions in your own environment.

To help illustrate how to build a polyglot solution, this guide presents a case study of a fictitious company faced with building a highly scalable web application capable of supporting many thousands of concurrent users.

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