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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

NoSQL databases

In our discussion of NoSQL types and databases, we will primarily focus on the following characteristics of NoSQL databases:

  • In-memory databases
  • Columnar databases
  • Document-oriented databases
  • Key-value databases
  • Graph databases
  • Other NoSQL types and summary

Most types of NoSQL used in the industry today fall into one or more of these categories. The next few sections will discuss the high-level properties of each of these NoSQL offerings, their main advantages, and products in the market that fall into the respective categories.

In-memory databases

In-memory databases, as the name implies, leverage the computer memory; that is, the RAM, to store datasets. Before we look into how in-memory databases work,...

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