Book Image

Getting Started with CockroachDB

By : Kishen Das Kondabagilu Rajanna
Book Image

Getting Started with CockroachDB

By: Kishen Das Kondabagilu Rajanna

Overview of this book

Getting Started with CockroachDB will introduce you to the inner workings of CockroachDB and help you to understand how it provides faster access to distributed data through a SQL interface. The book will also uncover how you can use the database to provide solutions where the data is highly available. Starting with CockroachDB's installation, setup, and configuration, this SQL book will familiarize you with the database architecture and database design principles. You'll then discover several options that CockroachDB provides to store multiple copies of your data to ensure fast data access. The book covers the internals of CockroachDB, how to deploy and manage it on the cloud, performance tuning to get the best out of CockroachDB, and how to scale data across continents and serve it locally. In addition to this, you'll get to grips with fault tolerance and auto-rebalancing, how indexes work, and the CockroachDB Admin UI. The book will guide you in building scalable cloud services on top of CockroachDB, covering administrative and security aspects and tips for troubleshooting, performance enhancements, and a brief guideline on migrating from traditional databases. By the end of this book, you'll have gained sufficient knowledge to manage your data on CockroachDB and interact with it from your application layer.
Table of Contents (17 chapters)
1
Section 1: Getting to Know CockroachDB
4
Section 2: Exploring the Important Features of CockroachDB
9
Section 3: Working with CockroachDB
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...