Presumably there's an entire data engineering / event processing pipeline that's being used to track user interactions at a fine grained level. These events are going to be aggregated and munged by various teams for things like business analytics, product / experiment feature analysis, ad analysis, as well as machine learning model feature development (just to name a few massive ones off the top of my head). Each of these will vary in their requirements of things like timeliness, how much compute is necessary to do their work, what systems / frameworks are used to do the aggregations or feature processing, and tolerance to failure.

> This is not apples to apples but Whatsapp

And yeah, whatsapp isn't even close to an apt comparison. It's a completely different business model with vastly different engineering requirements.

Is Twitter bloated? Perhaps, but it's probably driven by business reasons, not (just) because engineers just wanted to make a bunch of toys and promo projects (though this obviously always plays some role).