Feature flag systems are usually based on a set of rules that could be serialized and evaluated locally (this is how pretty much every open source feature flag

Feature flag systems are usually based on a set of rules that could be serialized and evaluated locally (this is how pretty much every open source feature flag system and feature flag SaaS works). Usually it's based on some kind of UUID being hashed with a per-flag seed and bucketed after some set of targeting rules are applied to other properties passed in for that user. There are added features where you can stores large cohorts to do specific targeting and usually there's some kind of local cache added to make that look-up faster for recent users. I'm not sure what the original commenter was doing but it sounds like they had some kind of targeting that was almost entirely based on cohorts or maybe they needed to have stability over time which would require a database. We did something similar recently except we just store a "session ID" with a blob for look-up and the evaluation only happens on the first request for a given session ID.