Stochastic Gradient Descent Batching
In SGD you just feed an example to your model, compute the gradient of the loss function of that example and update the weights according to the gradient of the loss of that example.

In mini-batch gradient descent you feed a batch to your model, compute the gradient of the loss of that batch and update the weights according to the gradient of the loss of that batch.

In fact, SGD is mini-batch gradient descent with batch size equal to 1.