Hi @uejimurashu ,
Welcome to the JMP Community pages. In short, the answer is no, they are not the same. JMP has several different tree-based platforms that all have slightly different algorithms and implementations to how the modeling is optimized, as well as the hyperparameters for the model. These include partitioning, boosted trees, bootstrap forest (similar to random forest), and extreme gradient boosted trees (XGBoost). The last one is an additional add-in, that I believe you need at least JMP Pro v16.0 or higher to run -- it could be v15.0.
You can find out more in JMP Help about boosted trees here, bootstrap forests here, and partitioning here. There's a good video on the different platforms here, and if you have Pro, then you can read up on XGBoost here.
Hope this helps!,
DS