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DevOps for Databases

You're reading from   DevOps for Databases A practical guide to applying DevOps best practices to data-persistent technologies

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781837637300
Length 446 pages
Edition 1st Edition
Concepts
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Author (1):
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David Jambor David Jambor
Author Profile Icon David Jambor
David Jambor
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Table of Contents (24) Chapters Close

Preface 1. Part 1: Database DevOps
2. Chapter 1: Data at Scale with DevOps FREE CHAPTER 3. Chapter 2: Large-Scale Data-Persistent Systems 4. Chapter 3: DBAs in the World of DevOps 5. Part 2: Persisting Data in the Cloud
6. Chapter 4: Cloud Migration and Modern Data(base) Evolution 7. Chapter 5: RDBMS with DevOps 8. Chapter 6: Non-Relational DMSs with DevOps 9. Chapter 7: AI, ML, and Big Data 10. Part 3: The Right Tool for the Job
11. Chapter 8: Zero-Touch Operations 12. Chapter 9: Design and Implementation 13. Chapter 10: Database Automation 14. Part 4: Build and Operate
15. Chapter 11: End-to-End Ownership Model – a Theoretical Case Study 16. Chapter 12: Immutable and Idempotent Logic – A Theoretical Case Study 17. Chapter 13: Operators and Self-Healing Data Persistent Systems 18. Chapter 14: Bringing Them Together 19. Part 5: The Future of Data
20. Chapter 15: Specializing in Data 21. Chapter 16: The Exciting New World of Data 22. Index 23. Other Books You May Enjoy

Summary

In this chapter, we’ve dived deep into the fascinating realm of large-scale data-persistent systems, covering everything from their historical origins to their modern-day complexities. We kicked things off with a stroll down memory lane, providing a brief history of how data persistence has evolved from rudimentary filesystems to sophisticated databases. We pondered the ever-changing needs of businesses and organizations that catalyzed this progression, establishing a solid foundation for understanding the subject.

Then, we shifted our focus to database evolution, focusing on the technical intricacies and the multifaceted growth databases have undergone over the years. From the days of hierarchical and network databases to the era of relational databases and their SQL foundations, we saw how the need to manage structured data led to the development of advanced systems capable of complex queries, indexing, and data integrity.

The chapter then took a significant...

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