You're reading from AWS for Solutions Architects Design your cloud infrastructure by implementing DevOps, containers, and Amazon Web Services

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781789539233

Length 454 pages

Edition 1st Edition

Tools

AWS

Concepts

Cloud Computing

Table of Contents (20) Chapters

Preface

1. Section 1: Exploring AWS

2. Chapter 1: Understanding AWS Cloud Principles and Key Characteristics FREE CHAPTER

3. Chapter 2: Leveraging the Cloud for Digital Transformation

4. Section 2: AWS Service Offerings and Use Cases

5. Chapter 3: Storage in AWS – Choosing the Right Tool for the Job

6. Chapter 4: Harnessing the Power of Cloud Computing

7. Chapter 5: Selecting the Right Database Service

8. Chapter 6: Amazon Athena – Combining the Simplicity of Files with the Power of SQL

9. Chapter 7: AWS Glue – Extracting, Transforming, and Loading Data the Simple Way

10. Chapter 8: Best Practices for Application Security, Identity, and Compliance

11. Section 3: Applying Architectural Patterns and Reference Architectures

12. Chapter 9: Serverless and Container Patterns

13. Chapter 10: Microservice and Event-Driven Architectures

14. Chapter 11: Domain-Driven Design

15. Chapter 12: Data Lake Patterns – Integrating Your Data across the Enterprise

16. Chapter 13: Availability, Reliability, and Scalability Patterns

17. Section 4: Hands-On Labs

18. Chapter 14: Hands-On Lab and Use Case

19. Other Books You May Enjoy

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A brief history of databases

Relational databases have been around for over 50 years. The first database was created by Edgar F. Codd in 1970. The main feature of a relational database is that data is arranged in rows and columns, and rows in tables are associated with other rows in other tables by using the column values in each row as relationship keys. Another important feature of relational databases is that they normally use Structured Query Language (SQL) to access, insert, update, and delete records. SQL was created by IBM researchers Raymond Boyce and Donald Chamberlin in the 1970s. Relational databases and SQL have served us well for decades.

With the increase in the popularity of the internet in the 1990s, we started hitting scalability limits with relational databases. Additionally, a larger variety of data types started cropping up. RDBMSes were simply not enough anymore. This led to the development of new designs. And with this, we got the fuzzy and confusing term...