Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-v5vhk Total loading time: 0 Render date: 2024-06-17T18:45:04.932Z Has data issue: false hasContentIssue false

15 - Big Data and NoSQL

Published online by Cambridge University Press:  26 April 2019

Parteek Bhatia
Affiliation:
Thapar University, India
Get access

Summary

Chapter Objectives

✓ To discuss the major issues of relational databases

✓ To understand the need for NoSQL

✓ To comprehend the characteristics of NoSQL

✓ To understand different data models of NoSQL

✓ To understand the concept of the CAP theorem

✓ To discuss the future of NoSQL

After about half a century of dominance of relational database, the current excitement about NoSQL databases comes as a big surprise. In this chapter, we'll explore the challenges faced by relational databases due to changing technological paradigms and why the current rise of NoSQL databases is not a flash in the pan.

Let us start our discussion by looking at relational databases.

The Rise of Relational Databases

Dr E. F Codd proposed the relational model in 1969. It was soon adopted by the mainstream software industries due to its simplicity and efficiency replacing hierarchical and network models that were prevalent at that time. The timeline showing the rise of the relational model is depicted in Figure 15.1.

The reasons for the success of relational databases were their simplicity, the power of SQL, support for transaction management, concurrency control, and recovery management.

Major Issues with Relational Databases

The relational data model organizes data in rows and columns that are arranged in a tabular form. In the relational model, a row is known as a tuple which is a set of key-value pairs and a relation is a set of these tuples. All operations in SQL consume and return relations. This foundation based on relations provides a certain elegance and simplicity, but it also suffers some limitations. The values in a relational tuple have to be simple (atomic)—they cannot contain any structure, such as a nested record or a list.

This limitation is not true for in-memory data structures, which can take on much richer structures than relations. As a result, if you want to use a richer in-memory data structure, you would have to translate it to a relational representation to store it on disk. This problem is known as impedance mismatch i.e. two different representations that require inter-translation as shown in Figure 15.2.

The impedance mismatch is a major source of frustration for application developers. In the 1990s many experts believed that impedance mismatch would lead to relational databases being replaced with databases that replicate the in-memory data structures to disk.

Type
Chapter
Information
Data Mining and Data Warehousing
Principles and Practical Techniques
, pp. 442 - 466
Publisher: Cambridge University Press
Print publication year: 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Big Data and NoSQL
  • Parteek Bhatia
  • Book: Data Mining and Data Warehousing
  • Online publication: 26 April 2019
  • Chapter DOI: https://doi.org/10.1017/9781108635592.016
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Big Data and NoSQL
  • Parteek Bhatia
  • Book: Data Mining and Data Warehousing
  • Online publication: 26 April 2019
  • Chapter DOI: https://doi.org/10.1017/9781108635592.016
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Big Data and NoSQL
  • Parteek Bhatia
  • Book: Data Mining and Data Warehousing
  • Online publication: 26 April 2019
  • Chapter DOI: https://doi.org/10.1017/9781108635592.016
Available formats
×