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Vitess: Introduction And New Features

2022-10-28

Authors:   Deepthi Sigireddi, Rohit Nayak, Matt Lord


Summary

Vitess is a cloud-native database solution that enables virtually unlimited scaling of MySQL. The architecture is based on key spaces and shards, and it includes components such as vt tablets, vtgate, and vtc tld. VReplication is a subsystem that enables seamless migrations, resharding, materialized views, CDC, job queues, and other data workflows. Vitess is highly scalable, available, and compatible with various MySQL flavors. Key users include JD.com and Slack.
  • Vitess is a cloud-native database solution that enables virtually unlimited scaling of MySQL
  • The architecture is based on key spaces and shards, and it includes components such as vt tablets, vtgate, and vtc tld
  • VReplication is a subsystem that enables seamless migrations, resharding, materialized views, CDC, job queues, and other data workflows
  • Vitess is highly scalable, available, and compatible with various MySQL flavors
  • Key users include JD.com and Slack
Vitess was initially developed as a MySQL scaling solution at YouTube, but it has evolved into a cloud-native database with CNCF graduated project. It was donated by Google to CNCF in January of 2018 as an incubating project and it graduated from CNCF in November of 2019. It was the eighth project to graduate from CNCF and the first storage project.

Abstract

Vitess is a cloud-native database solution that enables virtually unlimited scaling of MySQL. In this session we’ll first cover a high level overview of Vitess features, the architecture, and what database workloads are a good fit. We’ll then dive deeper into VReplication — the Vitess subsystem that enables seamless migrations, resharding, materialized views, CDC, job queues, and other data workflows. This is a big part of the value Vitess offers in empowering  infrastructure teams to manage a fleet of MySQL servers as a single logical database. We’ll conclude with demos of key VReplication workflows to illustrate how they make it easy to perform common data management tasks.

Materials:

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