All these dimension reduction methods are extremely similar. The math essentially just preserves nearest neighbors, with a setting for how 'tight' you want the clusters to be.

Check out this image [1] and accompanying paper [2] for further reference

[1] https://www.semanticscholar.org/paper/A-Unifying-Perspective...

[2] https://arxiv.org/abs/2007.08902