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AWS Certified Cloud Practitioner Exam Guide

You're reading from   AWS Certified Cloud Practitioner Exam Guide Build your cloud computing knowledge and build your skills as an AWS Certified Cloud Practitioner (CLF-C01)

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801075930
Length 630 pages
Edition 1st Edition
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Author (1):
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Rajesh Daswani Rajesh Daswani
Author Profile Icon Rajesh Daswani
Rajesh Daswani
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Table of Contents (23) Chapters Close

Preface 1. Section 1: Cloud Concepts
2. Chapter 1: What Is Cloud Computing? FREE CHAPTER 3. Chapter 2: Introduction to AWS and the Global Infrastructure 4. Chapter 3: Exploring AWS Accounts, Multi-Account Strategy, and AWS Organizations 5. Section 2: AWS Technologies
6. Chapter 4: Identity and Access Management 7. Chapter 5: Amazon Simple Storage Service (S3) 8. Chapter 6: AWS Networking Services – VPCs, Route53, and CloudFront 9. Chapter 7: AWS Compute Services 10. Chapter 8: AWS Database Services 11. Chapter 9: High Availability and Elasticity on AWS 12. Chapter 10: Application Integration Services 13. Chapter 11: Analytics on AWS 14. Chapter 12: Automation and Deployment on AWS 15. Chapter 13: Management and Governance on AWS 16. Section 3: AWS Security
17. Chapter 14: Implementing Security in AWS 18. Section 4: Billing and Pricing
19. Chapter 15: Billing and Pricing 20. Chapter 16: Mock Tests 21. Answers 22. Other Books You May Enjoy

Learning about additional database services for specific niche requirements

In addition to Amazon RDS and DynamoDB, AWS also offers additional databases that meet the requirements of specific niche applications. In this section, we will take a look at two of those databases: Amazon Neptune and Amazon Quantum Ledger Database (QLDB).

Introduction to Amazon Neptune

Amazon Neptune is a fully managed graph database service and a type of NoSQL database. Graph databases are designed to store data as nodes (person, place, location, and so on) and directions. Each node would have some property and nodes have relationships between them. So, for example, Alice lives in London, and in London, there is a resident called Alice. This is a simple example, but you can start to imagine how complex your nodes and their relationships can become. These kinds of complex relationships between the nodes are just as important as the data itself and are ideal for a graph database solution. Traditional...

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