Fast way to classify very large dataset

I have a very large dataset of about 150M samples and 9 predictors. Every sample belongs to one of nine classes, and the class sizes are balanced. What is the fastest way in Matlab (2016b) to train a machine learning model able to predict the correct class for a new sample? I tried TreeBagger with 100 trees, but this is very slow.