How do tech-companies employ Random Forest on large data sets?
For the Random Forests algorithm, the time complexity for building a complete un-pruned tree is $O(m.n\log(n))$, where $n$ is the number of records/instances and $m$ is the number of variables. The algorithm is embarrassingly parallel so in many cases companies with available resources will simply use sufficient compute nodes to enable the model to run in a time that they consider reasonable.