Confused about CatRegressor feature importance vs SHAP

I'm confused about result from a CatBoostRegressor-model. I follow this article: https://towardsdatascience.com/catboost-regression-in-6-minutes-3487f3e5b329

My confusion is about the difference in order of the variables in the figure CatBoost Feature Importance and the Shapley Additive exPlanations (SHAP) plot. When I lab with other datasets I get even bigger differences between these two plots. Why can they differ? And what does it say about feature importance when one variables scores high on one and low on another?

My own result.