evaluating clustering algorithms?

We are working on text clustering for the data science project we find a few algorithms that can work with text like

-K-means

-K-medoids 

These two are centroid clustering and we use Davies Bouldin evaluation metrics to evaluate them  

-Agglomerative clustering

-Top-down clustering

These two are hierarchical clustering but we don't know how to evaluate them we need to compare between these four, so we need to find unified evaluation method