vitess VS go-mysql-server

With Vitess likely merging a lot of its binaries into a single unified binary: https://github.com/vitessio/vitess/issues/7471#issuecomment-...

... it would be a wild future if Vitess replaced the underlying MySQL engine with this as long as the performance is good enough.

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. Once we make that change, we can look towards supporting recursive CTEs.

This however will take some time, but then, all good things do!

Why would it be a Google project? https://github.com/vitessio/vitess

This is great news. I strolled around https://github.com/vitessio/vitess/issues/12967.

Are there any public discussions of more trade-offs vitess has to make to enable fks?

MySQL + Vitess I noticed Slack gets by using MySQL because they're using Vites. From Slack's post (https://slack.engineering/scaling-datastores-at-slack-with-vitess/) it seems like they choose Vites because it facilitated a smooth transition because it's built on top of MySQL.

This sounds very similar to the connection pooling done by vitess https://vitess.io/.

https://github.com/vitessio/vitess/issues/12967

A lot of this is possible thanks to the magic of Vitess.

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

https://github.com/vitessio/vitess

We implemented a query optimizer with a flexible intermediate representation in pure Go:

https://github.com/dolthub/go-mysql-server

Getting the IR correct so that it's both easy to use and flexible enough to be useful is a really interesting design challenge. Our primary abstraction in the query plan is called a Node, and is way more general than the IR type described in the article from OP. This has probably hurt us: we only recently separated the responsibility to fetch rows into its own part of the runtime, out of the IR -- originally row fetching was coupled to the Node type directly.

This is also the query engine that Dolt uses:

https://github.com/dolthub/dolt

But it has a plug-in architecture, so you can use the engine on any data source that implements a handful of Go interface.

Might be interested in https://github.com/dolthub/go-mysql-server, which also does this

https://github.com/dolthub/go-mysql-server

One item under "Scope of this project":

Provide a runnable server speaking the MySQL wire protocol, connected to data sources of your choice.

I just wanted to say thanks for https://github.com/dolthub/go-mysql-server

This is incredibly useful for anyone who wants to build their own DB or wrap another datasource so it's queryable via MySQL protocol.

a very cool project they also maintain is a MySQL server framework for arbitrary backends (in Go): https://github.com/dolthub/go-mysql-server

You can define a "virtual" table (schema, how to retrieve rows/columns) and then a MySQL client can connect and execute arbitrary queries on your table (which could just be an API or other source)

Thanks for this write up! I've been really interested in postgres compatibility in the context of a tool I maintain (https://github.com/mergestat/mergestat) that uses SQLite. I've been looking for a way to expose the SQLite capabilities over a more commonly used wire-protocol like postgres (or mysql) so that existing BI and visualization tools can access the data.

This project is an interesting one: https://github.com/dolthub/go-mysql-server that provides a MySQL interface (wire and SQL) to arbitrary "backends" implemented in go.

It's really interesting how compatibility with existing protocols has become an important feature of new databases - there's so much existing tooling that already speaks postgres (or mysql), being able to leverage that is a huge advantage IMO