# Why SOM is better than clustering technique(e.g. hierarchical)?

I am using SOM for dimension reduction and visualization purpose (to put the same observations together). I am using kohonen r-package for the same.

https://cran.r-project.org/web/packages/kohonen/kohonen.pdf

For experimental purpose I took a 2-dimensional data (original):

1. Applied hierarchical clustering on original data.
2. Applied SOM on original data and then applied hierarchical clustering on top of that.

I got similar results.

So my question is: Is preserving the topological distances only advantage behind using SOM over clustering?

If yes, then why this is important? If no, what are other advantages of SOM over clustering?