It is capable of dealing with both continuous and discrete data. It can handle a large number of predictors and data points. It is quick and can be used to make predictions in real time. It is unaffected by non-essential characteristics.
The generative model Naive Bayes is. (Gaussian) Each class in Naive Bayes is assumed to have a Gaussian distribution. The distinction between QDA and (Gaussian) Naive Bayes is that Naive Bayes assumes feature independence, resulting in diagonal covariance matrices.