Our analysis of molecular fingerprints in the natural product chemical space shows that algorithms belonging to the same category tend to be highly correlated, but they strongly diverge in terms of classification performance, pairwise similarities and chemical space representation when comparing them across categories. This finding suggests that when choosing which encoding to use for cheminformatics applications, it is beneficial to sample multiple fingerprints belonging to different classes to maximize diversity.