I suspect there’s a bit of confusion with the readme saying that DecisionTree.jl supports scikitlearn’s API; that does not mean it calls scikit learn; it means it can be called from ScikitLearn.jl which is a wrapper for the python library scikit-learn as well as for a number of other models (apologies if I misunderstood your question)
And yes DecisionTree.jl is entirely written in Julia. As for the performances, can you clarify what you’re comparing with? are you comparing with scikit-learn’s random forest? If so then IIRC scikit-learn’s ensemble models are a bit slow and so seeing a 1.5x performance improvement would not be too surprising.