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Getting Started with CockroachDB

You're reading from   Getting Started with CockroachDB A guide to using a modern, cloud-native, and distributed SQL database for your data-intensive apps

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781800560659
Length 246 pages
Edition 1st Edition
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Author (1):
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Kishen Das Kondabagilu Rajanna Kishen Das Kondabagilu Rajanna
Author Profile Icon Kishen Das Kondabagilu Rajanna
Kishen Das Kondabagilu Rajanna
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Getting to Know CockroachDB
2. Chapter 1: CockroachDB – A Brief Introduction FREE CHAPTER 3. Chapter 2: How Does CockroachDB Work Internally? 4. Section 2: Exploring the Important Features of CockroachDB
5. Chapter 3: Atomicity, Consistency, Isolation, and Durability (ACID) 6. Chapter 4: Geo-Partitioning 7. Chapter 5: Fault Tolerance and Auto-Rebalancing 8. Chapter 6: How Indexes Work in CockroachDB 9. Section 3: Working with CockroachDB
10. Chapter 7: Schema Creation and Management 11. Chapter 8: Exploring the Admin User Interface 12. Chapter 9: An Overview Of Security Aspects 13. Chapter 10: Troubleshooting Issues 14. Chapter 11: Performance Benchmarking and Migration 15. Other Books You May Enjoy Appendix: Bibliography and Additional Resources

Introduction to geo-partitioning  

As the word geo-partition suggests, the data is partitioned based on geographical locations. Geo-partitioning refers to the mechanism of storing the data in various geographical locations, based on where the data is being consumed.

For example, let's say you are maintaining a database for an airlines company that has international and domestic travelers as its users from every continent. Since they have a global presence, it would be beneficial to keep the users' data close to where they live. This will help in serving the data locally and quickly.

Figure 4.1 shows an example of a table whose rows are partitioned based on geo-location across three different continents. Rows are stored in specific databases based on their locality. This locality can be mapped to the user's location based on their activity:

Figure 4.1 – An example of a geo-partitioned table

Geo-partitioning will be...

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