Quantify the amount of differences of one data set to another
Just average (or pool, moree generally aggregate) some of the standard measures:

if you look closly python implementation is already general for some of them, meaning that you can apply them directly on dataset and not individually on the vectors

Examples: Cosine similarity, Eucledian distance, Manhattan/city-block distance, Chebychev distance, Minkowsky dustance. For computer vision, similarity measures are: Hausdorff Distance (the two data vectors will be considered close if every point of each set is close to some point of the other set), Bhattacharyya Distance (measure of similarity of two probabilty distributions), Bhattacharyya coefficient (measure of relative closeness of the two vectors) and Mahalanobis Distance (a specific case of Bhattacharyya Distance).