If your data doesn't require preprocessing ... Very often you need to prepare data to use xgboost/lightgbm. You need to fill missing values, convert categoricals/dates/text to numeric, do feature engineering.

What is more, MLJAR AutoML is checking much simpler algorithms for you, like Dummy Models (average response or majority vote), linear models, simple decision trees - because very often you don't need Machine Learning. The xgboost/lightgbm cant do this :)