The idea of doing predictive ML inside of, say, MySQL, sounds tremendously appealing. E.g. if you could add something like a "predictive index" that would model one column based on certain other columns, and with a variety of "prediction types" (just like choosing index types of b-tree, hash, etc.).

Although instead of a SELECT statement on existent rows, you'd need to use something like a PREDICT statement on non-existent rows:

  PREDICT product_category
  FROM invoice_data
  WHERE item_description = "Packaging design"
  AND vendor_code = "VENDOR-1676"

The big question for me, however, would be: when would the predictive model be updated? It seems too computationally expensive to update it on every UPDATE, INSERT and DELETE. I mean, if it's of any decent complexity, it would require a full table read every time it was updated, no? Would you have to manually issue a command to update it? How long would that take?

But it absolutely seems like a very natural place to predictive capabilities -- directly into the database.