[george3d6]

From the user perspective it's inside the database, you can run mindsdb in the backgrond,connect it to the database once, and then do everything from within the database (i.e. connecting with a sql client to your database server and issuing commands the same way you would query "normal" tables).

From a technical perspective it's a separate server that communicates with the database through various mechanisms (e.g. federate engine) but it's no different from e.g. multiple instance of mariadb being abstracted by a galera cluster into something that behaves like a single database from a client perspective.

[michaelpb]

Gotcha, yeah not who were replying too, but I read/skimmed most of your post first thinking was a new DBMS specifically for machine learning (especially given the name), which is a lot less interesting to me and I was about to close the tab. I much prefer the phrasing you used on the GitHub, I think it's more clear: "Predictive AI layer for existing databases"

Anyway, I'm seriously going to look into using this on a product for work, thanks for sharing & your work on this! We are in the process of triaging a few different features for a product in education (can chat more about it if your curious!), including some fairly bog-standard predictive text features. We are also trying to avoid strictly depending on any one proprietary PaaS, so this might just fit the bill!

[george3d6]

We are honestly very happy to hear about every usecase people have for this right now. It's users that help us shape the product to a large extent, at the end of the day.

We can chat more about it here or feel free to pick one of the many contact routes scattered around the thread :)

What's the name of the product? What does it do?

[robertlagrant]

Sure, from a client perspective that makes sense, but it misled me a bit. I thought the DBMS was running the ML, a bit like an ML equivalent of a materialised view.