Co-joining multi-peak histograms
One option is Kullback–Leibler divergence which is a measure of how one probability distribution is different from a second probability distribution.

Kullback–Leibler divergence compares the entire distribution (not just peaks) and does not make any assumptions of the functional form of the distribution (which is useful since your data is not very Gaussian).

In fact, Kullback–Leibler divergence can compare discrete distributions so you do not need to fit a Kernel Density Estimation (KDE) curve.