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vitessio
vitess
Go2014–2026
vitessio / vitess

vitess

Vitess is a database clustering system for horizontal scaling of MySQL.

Data & DatabasesSystems & InfrastructureDevOps & Cloud
Explore on GitHubRead Hacker News discussions
47Distinct people
53Mentions
0Explicit recommenders
21.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Vitess is a database clustering system for horizontal scaling of MySQL.

GitHub

Where it is used

  • Slack — “How Slack leverages Vitess to keep pace with ever-growing storage needs” Source
  • JD.com — “We now run MySQL databases in containerized environments with Kubernetes and use Vitess for scalable cluster management and handling large volumes of complex transactional data.” Source

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year53 dated mentions

Observed mentions: 2014-02-03 10:41:47 UTC to 2026-02-20 17:58:18 UTC.

02468102014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 9 mentions; 3 submissions, 6 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 3 mentions; 2 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 6 mentions; 0 submissions, 6 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC936
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC716
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC202
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC211
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC312
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC321
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC303
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC404
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC514
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC606
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC404
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC303

From the project README

An excerpt from the repository, fetched Nov 13, 2026.

Read the project’s introduction
Vitess Vitess is a cloud-native horizontally-scalable distributed database system that is built around MySQL. Vitess can achieve unlimited scaling through generalized sharding. Vitess allows application code and database queries to remain agnostic to the distribution of data onto multiple database servers. With Vitess, you can even split and merge shards as your needs grow, with an atomic cutover step that takes only a few seconds. Vitess was a core component of YouTube's database infrastructure from 2011, and grew to encompass tens of thousands of MySQL nodes. Starting in 2015, Vitess was adopted by many other large companies, including Slack, Square (now Block), and JD.com. For more about Vitess, please visit vitess.io. Community Vitess has a growing community. If you are interested in contributing or participating in our monthly community meetings, please visit the Community page on our website. We also maintain a roadmap on our website. Follow our blog for low-frequency updates like new features and releases. Reporting a Problem, Issue, or Bug To report a problem, create a GitHub issue. For topics that are better discussed live, please join the Vitess Slack workspace. You may post any questions on the #general channel or join some of the special-interest channels. Security Reporting Security Vulnerabilities To report a security vulnerability, please email vitess-maintainers. See Security for a full outline of the security process. Security Audit A third party security audit was performed by ADA Logics. Read the full report. License Unless otherwise noted, the Vitess source files are distributed under the Apache Version 2.0 license found in the LICENSE file.
Read the full README on GitHub

What Hacker News says

53 sources
mattlord·Feb 20, 2026
It's open source. If you really want to know these things, I would encourage you to look at the code and read the documentation. As noted in the blog post, reverse vreplication is setup when you switch. You can switch back and forth and nothing is lost. https://github.com/vitessio/vitess https://vitess.io/docs/reference/vreplication/ "isn't this just pushing the same issue forward in time?" I don't understand what you are trying to say here. You can only compare the two sides / databases at the same logical point in time. While you are doing this comparison at that point in time, the timeline continues to progress. Unless you want to stop the world and prevent writes for the full duration of the diff (which can be days or even weeks).
In Zero downtime migrations at petabyte scale (2024)
guptamanan100·Dec 5, 2023
Thank you for the compliment! We recently started adding support for CTEs in Vitess! You can check out https://github.com/vitessio/vitess/pull/14321 if you want to see some technical details of the implementation. For now, we have added preliminary support by converting them to derived tables internally, but we believe that we need to make CTEs first-class citizens themselves of query planning, specifically because recursive CTEs are very hard to model as derived tables. Once we make that change, we can look towards supporting recursive CTEs. This however will take some time, but then, all good things do!
In The challenges of supporting foreign key constraints

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