1. https://stats.stackexchange.com/questions/141165/difference-between-k-medoids-and-pam:

k-medoids is the problem specification. It may be a np-hard problem.

PAM is one algorithm to find a local minimum for the k-medoids problem. Maybe not the optimum, but faster than exhaustive search.

PAM is to k-medoids as Lloyd's algorithm is to k-means. Lloyd's algorithm is a fast heuristic to find a good solution to k-means, but it may fail to find the best.

2. Mixed data types

https://towardsdatascience.com/clustering-datasets-having-both-numerical-and-categorical-variables-ed91cdca0677
https://towardsdatascience.com/clustering-on-mixed-type-data-8bbd0a2569c3
https://datascience.stackexchange.com/questions/22/k-means-clustering-for-mixed-numeric-and-categorical-data

3. Select K

https://towardsdatascience.com/silhouette-or-elbow-that-is-the-question-a1dda4fb974