I don't think that's right. If you have enough data points, your prior gradually gets more relevant. And Bayesian statistics has the concept of an "ignorance prior", which mathematically represents the position where all possibilities are equally likely. Bayesian statistics also offers the possibility of adding more data after running your experiment, and computing a new answer in a consistent way. Whereas doing this with frequentist statistics completely is completely invalid.