The differences between SVM and Logistic Regression

Question

I am reading about SVM and I've faced to the point that non-kernelized SVMs are nothing more than linear separators. Therefore, is the only difference between an SVM and logistic regression the criterium to choose the boundary?

Apparently, SVM chooses the maximum margin classifier and logistic regression is the one that minimizes the cross-entropy loss. Are there situations where SVM performs better than logistic regression or vice-versa?