You're reading from AWS Cloud Computing Concepts and Tech Analogies

Product type Book

Published in Apr 2023

Publisher Packt

ISBN-13 9781804611425

Pages 358 pages

Edition 1st Edition

Languages

Concepts

Cloud Computing

Authors (3):

Ashish Prajapati

Juan Carlos Ruiz

Marco Tamassia

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Table of Contents (22) Chapters

Preface

1. Part 1: Cloud Infrastructure and Core Services

2. Chapter 1: Understanding Cloud Computing – Demystifying the Cloud

3. Chapter 2: Global Infrastructure behind Cloud Platforms – What Is the Cloud Made of?

4. Chapter 3: Computing – In Cloud We Trust, Everything Else We Compute

5. Chapter 4: Storage – Where Should I Keep My Data and Maybe Publish It?

6. Chapter 5: Networking – So, How Do I Get Inside, Outside, and Across the Cloud?

7. Part 2: Platform Services

8. Chapter 6: Databases – To SQL or Not to SQL for So Many Records…

9. Chapter 7: Identity and Access Management – Who Am I and What Can I Do?

10. Chapter 8: Monitoring – Is Big Brother Watching?

11. Chapter 9: Scalability – I Scale to the Moon and Back

12. Part 3: Application Services

13. Chapter 10: Automation – Look, My Infrastructure Is in Code!

14. Chapter 11: Decoupled Architectures – in Space and Time

15. Chapter 12: Containers – Contain Yourself and Ship Some Containers

16. Chapter 13: Serverless – So, Where Are My Servers?

17. Chapter 14: Caching – Microseconds Latency: Why Are We Always in a Rush?

18. Chapter 15: Blockchain – Who Watches the Watchmen?

19. Chapter 16: What the Future Holds

20. Index

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Non-relational databases

After the break, Berta wants to finish her explanation with non-relational databases. As there are several types that she wants to talk about, she starts as soon as possible.

Berta: AWS also offers different non-relational databases, and there are many of them. Each one of them is suited to a specific use case, for example, graph databases.

Alex: These are for graphics?

Berta: No, graph, not graphics. You can store different entities and the relationships between them, building a complex graph. They can be used in recommendation engines, fraud detection, identity graphs, and similar applications. For that purpose, Amazon Neptune would be the right choice.

You can also have databases in RAM, for extreme performance, or databases that are time-based, where you analyze time series, such as for the Internet of Things, stock prices, measurements such as temperature or pressure, or...