Hi BattySeahorse19 !
We have made a comparison, https://clear.ml/blog/stacking-up-against-the-competition/ but as this industry moves in lightning-speed, this is probably already outdated 🙂
I am not closely following MLFLow so some of the features I'll discuss below might be outdated but the gist of it is this:
ClearML has an orchestration part, data management, serving, pipelines, Hyperparameter optimziation while MLFlow doesn't. ClearML offers a hosted Saas while MLFlow needs to be served by yourself. IIRC, ClearML supports more graphs types and has more features around downloading them, better comparing information and so on.
These are I think the big ticket items, there are more, and each tool gives a little different feeling when using it.

AnxiousSeal95 ClearML has orchestration part, does it mean it can replace k8s deployment?

BattySeahorse19 replacing k8s is a very tall order 🙂 What ClearML means when it says orchestration is taking for the environment for running experiments. This is achieved by using ClearML Agent which, once installed, can fetch tasks from execution queues (which allows you to build management on top such as fairness, load distribution and so on). Once a task is fetched it takes care of everything it needs, from cloning the repository to installing dependencies to pulling specific dockers. The aim of the Agent is to make remote machines accessible for users without needing to preconfigure them.