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Hey! One of the maintainers of Feast here, mainly to make some friendly corrections on Feast’s functionality (e.g. Feast does in fact manage transformations) :)

Feast currently supports a few kinds of transformations: on demand transformations and streaming transformations. We’re adding batch transformations soon though! (and have an RFC out already).

I like to think that Feast’s goal is to be more of a pluggable framework for platform teams to be able to build towards a platform like Tecton’s (which fully orchestrates both batch and streaming transformations while abstracting complexity away from data scientists). We’re being mindful of trying to keep things as simple as possible though because our users have told us repeatedly they don’t want to forced to manage a complex system.

With moving features from the offline to online store (we call this materialization), users today can (and often quite successfully) use Feast’s CLI or SDK to trigger in memory materialization to the online store. We do have ongoing work to enable out of process materialization (e.g. using Ray, Spark, Bytewax, etc) that should be ready soon. Being able to manually trigger materialization via Airflow though has proven to be very useful for users in integrating with their existing workflows (such as triggering this when they detect changes to their raw data sources).

Simba’s correct though in calling out that a lot of the orchestration in Feast is left to the user. It hasn’t fully emerged as a key painpoint users want addressed, but if that changes… well we’re working to make our community happy :)

Cheers, Danny