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NoSQL databases offer more flexible alternatives to mainstream relational software, particularly for big data applications. But NoSQL offerings include a diverse set of technologies that can present prospective users with a bewildering array of choices. And those technologies have yet to secure a place in many organizations. In fact, in a survey of IT and business professionals conducted by The Data Warehousing Institute in November 2013, 65% of the respondents said they had no plans to incorporate NoSQL databases into their data warehouse architectures. Don't let that scare you off, though: There are companies successfully putting NoSQL products to work in applications they're suited for.
In this three-part guide, readers will learn about the different types of NoSQL technologies and their potential uses. First, get details about the four primary NoSQL product categories, with deployment examples from experienced users and advice on how to avoid going down the wrong database path. Next, read about why it's a mistake to force-fit technologies into IT environments -- and why Gartner analyst Merv Adrian says it's a fruitless exercise to compare NoSQL offerings "that are so wildly different in structure and intent." And in our third story, find out why many organizations are creating what consultancy Enterprise Management Associates calls a hybrid data ecosystem -- a blend of old and new technologies, including NoSQL systems -- to support their big data environments. Access >>>
Table of contents
- Varied NoSQL options need careful weighing, sorting
- Fit by fit, NoSQL databases vie to displace RDBMSes
- NoSQL just one part of IT mix on big data projects
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