Logistic regression can easily be made online too, keep in mind! sklearn has an implementation of online gradient descent, and vowpal wabbit is also excellent at those problems.
Naive bayes can be parallelized in ways that SGD can't, that's a whole other conversation.
Gradient descent can be made online. But it's very slow and suffers from catastrophic forgetting. Typical gradient descent needs to iterate over the dataset many times, while naive Bayes only needs one pass.
Naive bayes can be parallelized in ways that SGD can't, that's a whole other conversation.