[D] SGD for NNs vs SGD for svms (SGD = stochastic gradient descent)

I was wondering about the following and maybe it s an easily answerable question for some. So for training NNs as far as I know one usually uses some variant of SGD. For SVMs SDG also exists and is called pegasos as far I know. One step foe calculatinf the gradient or doing backprop requires quite some computation. The same goes for SVMs in SGD as we need to evaluate the kernel at many samples.
So my question is how …

gradient machinelearning nns stochastic