Deepthi, tech lead for Vitess, just published this RFC a few days ago: https://github.com/vitessio/vitess/issues/7084
Vitess plans to support PostgreSQL, but there is no work on that at this time.
In Scaling Datastores at Slack with Vitessvitessio
vitess
Go2014–2026
vitessio / vitess
vitess
Vitess is a database clustering system for horizontal scaling of MySQL.
47Distinct people
53Mentions
0Explicit recommenders
21.4KGitHub stars
What to know before exploring
What it is
Vitess is a database clustering system for horizontal scaling of MySQL.
GitHub
Where it is used
What people are saying
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Also in these discussions
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This week on Hacker News
Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 9:01:12 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.
* 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
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2014 | 2014-01-01 00:00:00 UTC | 2015-01-01 00:00:00 UTC | 9 | 3 | 6 |
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 7 | 1 | 6 |
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 3 | 2 | 1 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 5 | 1 | 4 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 6 | 0 | 6 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 3 | 0 | 3 |
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 GitHubWhat Hacker News says
3 sourcesThis is exactly what I did in the beginning :)
But custdev showed that companies do not care about it.
They are ready to take Django/RoR/Laravel developers who know only ORM. Such developers are cheaper, they are easier to hire.
Some people also think that it's faster to develop this way :)
They prefer to start dealing with problems after they get on production DB.
They shift developer problems to DBA. There is research saying that the price of fixing a bug in production is on average 400 times the price of fixing it at the development stage.
Ok, the boss call the shots :) I had to make a pivot to DBA needs.
It was a bit upsetting at first, but then I realized that it was even simpler. You need to do a lot more tools for developers to make them feel comfortable.
A few words about open source.
At first, I used this AST parser for PostgreSQ
Read the rest
L
https://github.com/lfittl/libpg_query
But it's frozen on Postgresql 10. And we don't know if there'll be any updates.
No official AST parser for MySQL.
There's a hard way to get a bison/ANTLR grammar parser.
Two weeks ago there was a parser like this for MySQL:
https://github.com/stevenmiller888/ts-mysql-parser.
There's also a parser from vitess:
https://github.com/vitessio/vitess/tree/master/go/vt/sqlpars...
The only problem is that the grammar for these parsers was written by hand and is not related to the official MySQL repository.
For example, the vitess parser does not support the syntax of MySQL 8.0, and MySQL 5.7 does not support more than 40%.
There is also such a tool https://www.jooq.org/.
It supports some of its own generalized SQL syntax, which does not take into account the specifics of different databases.
Look, there is another tool that uses libpg_query - sqlc:
https://news.ycombinator.com/item?id=21765689.
And the author of ts-mysql-parser also offers an analyzer:
https://github.com/stevenmiller888/ts-mysql-analyzer
There are only four rules at the moment...
Anyway, all hard work starts after you have the right AST parser in your hands. And if you don't spend all your time on it, it will be difficult for you to do something really interesting :(
PS: I removed the types exporting tool from the site a few days ago, along with texts explaining all the advantages of this tool to the developers :)
In a couple of weeks, I will transfer it to a separate domain, as a separate project.
I am open to personal communication outside this site, all my contacts are at https://holistic.dev/en/contacts/
> They don't scale to Google or Facebook operational sizes.
You may or may not know this, but the primary datastore used at both Google and FB is MySQL. Sure, they use replication and sharding, but I would strongly argue that MySQL with sharding scales better than some multi master NoSQL thing like Cassandra.
Related, you should check out https://github.com/vitessio/vitess if you haven't seen it. It's what Youtube and others use for their primary data store in production.
In Domain Logic and SQL (2003)