> What if you need to recompute this feature daily, for millions of customers and orders?...moreover, the DS/ML folks want the same feature but for "every 1/3/7/30/90/180/365/730/etc." days breakdown, as well as a bunch of variations about orders and things other than orders (e.g. "average time between new orders, over past 7/30/90 days" or "average $ spent over past 7/30/90 days", as features that serves as a proxy for frequency of activity and level of engagement)

...what data warehouse/database are you using that can't support those queries on-demand at low-latency and granularity?

It seems to me that these 'feature stores' are just tables of pre-computed common aggregates, optionally with some kind of versioning id/timestamp. In which case, why do I need some special service to do this, can't I just make a second database in my warehouse and write something that just computes all desired aggregations periodically and dumps them into the second db? Even easier, just use stored process and distribute them to data scientists, and use timestamp parameters to control versioning.