The real differentiation will come from feature engineering. Random forests and boosted trees (the other fire-and-forget model of choice) can tell you a lot about the data set from their validation performance under tuning. It might be that you've got a straightforward situation, but often the next step is to dig into what the model is doing and see if you can better optimize the features.