This kind of stuff is why rails is so productive for a normal web app. Sure, there are better vendor and point solutions for each of these, but the ability to drop in a gem, do some configuration and have a 80% solution lets you ship so. damn. fast.
Ahoy, blazer and field_test form the basis of our very strong no-BS data infra. It is so simple.
I still want to try and combine ahoy with a column store in postgres so that we can run the analytical queries straight onto postgres instead of syncing the events to BigQuery.
I've tried using pg_analytics by Paradedb but they don't support json columns, which is necessary with ahoy. Performance wise that would be ideal though.
And blazer[0], the closest thing to a perfect BI tool. It has a SQL editor/runner, saved queries, audit history, dashboards, alerts and user access control; all in a rails engine you can mount with minimal configuration.
Blazer is my favourite BI tool by a country mile. It does all I want with no fuss, is a breeze to set up and it's so much faster and more efficient than any of the other BI tools I've tried.
PgHero is also from him I believe. Very helpful to identify slow queries in production, remove duplicate indexes, see missing indexes, keep an eye on table size, etc.
For anyone using Ruby who doesn't know ankane already, there are some very useful tools in his github ... like /disco which is a super simple collaborative filtering implemention if you want to quickly drop some recommendation in somewhere
If you are looking for anything ML related with Ruby ankane has usually had a look already ...
Plus a bunch of other stuff[3].
Maybe he solved AI/ML by himself long ago and is using that to be this productive.
[0] https://github.com/pgvector/pgvector
[1] https://github.com/pgvector/pgvector-ruby
[2] https://github.com/ankane/neighbor
[3] https://github.com/ankane/