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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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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

Managing schema changes

CockroachDB supports online schema changes, which don't require any downtime. An existing schema can be changed using statements that include ALTER and CREATE INDEX operations.

CockroachDB internally maintains a consistent distributed schema cache, along with consistent table data that works with multiple versions of the schema concurrently. This enables the rolling out of a new schema while the older schema is still being used. CockroachDB backfills the table data into the newer schema without holding locks. So, online schema changes don't affect the current read/write operations on the cluster on a particular table whose schema is being modified.

Here are some of the benefits of online schema changes:

  • Zero downtime.
  • Schema changes happen without holding any table-level locks, so application workloads on the cluster can continue to operate without performance degradation.
  • Data is kept consistent throughout the schema upgrade...
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