The biggest historical obstacle to Bayesian stats was low amounts of data available and difficulty of computation. Frequentist stats is optimised around these. With 30 samples and very easy computations, you are able to produce a reasonable frequentist confidence interval, sometimes even with less data. On the other hand, even the simplest Bayesian analysis of determining the probability of heads in a coin flip requires some interesting integration and the somewhat obscure Beta distribution.

Now that we have lots of data and lots of computing power, Bayesian stats can show its results, after getting rebranded as "machine learning".