Should output data scaling correspond to the activation function's output?
What you read hold true for the neurons of the output layers and not for the hidden layers!

Hence, its true that if you are using tanh in output layers then you need the data labels to be within [-1, 1] where as between [0, 1] for sigmoid.

As for your concern with relu, use it on output layers if you know that the range of the labels of the data is positive only. If you are using relu in hidden layers then the scaling doesn't depend on relu but rather on the type of activation function used in output layers.