The Periodic Table (PT) is perhaps the most famous and widespread icon of chemistry. It orders chemical elements by their nuclear charge and groups them into families according to their similarity. Such arrangement was built using data about formulae of few compounds available in 19th century. Since then, the number of compounds has grown exponentially during the 20th and 21st centuries, and new types of compounds have been obtained that were unknown to pioneers, rising the question about the validity and generality of the PT. Can these patterns be extracted from current data or are they constrained to a particular chemical domain? To answer this question we conducted a Big Data exploration of chemical similarity using formulae of compounds reported since around 1800. We found that the similarities between elements of the same family are resilient to attacks and are ubiquitous along chemical contexts. We also found that PT groups approach true equivalence classes, being the most symmetrical and transitive on our data. These features point to an underlying structure in the PT ruling the similarity between elements, which agrees with its fundamental nature. Time analysis revealed that since around 1980 all similarity relations are waning by an increasing production of unique formulae on almost all elements, leading to a singularization of elements. Nonetheless, PT families tend to be more frequently found, showing they prevail over any other similarity pattern.