Hey! DVC maintainer here. I would say they overlap to some extent, but mostly complement each other for now. And that's what we see across our user base. MlFlow is used mostly as a ML logger - you insert some Python code into your scripts and log to MlFlow everything related to an experiment. While DVC is strong is managing and versioning data and models with a Git-like experience.