Which algorithm is better Eclat or Apriori and why?

Question

data mining

Hi all! I just can’t understand which algorithm for constructing association rules is better? Apriori or Eclat? Conducted an experiment in RStudio, building rules with support from 0.1 to 0.00001 using Eclat and Apriori. Eclat quickly created rules, while Apriori, starting from the support value of 0.0001, just hung (or rather, RStudio hung). Concluded that Eclat creates rules more quickly at low levels of support. Now we need to make one more experiment, I just started to increase the amount of data by duplication, I left the support value unchanged. I went from 10k data to 500k, only the time for reading the .csv file increased, and the Eclat and Apriori algorithms build rules equally quickly. Is it supposed to be like that? And why is Apriori considered the main algo along with FP-growth if Eclat is faster with decreasing support value?