Is the usage of the "momentum" significiantly superior to the conventional weight update
Using momentum is a noise reduction (noisy gradients) and signal amplification strategy.
Imagine a large hill with a rough terrain with lots of ups-and-downs. We are trying to navigate to the bottom of the hill by using purely local information. A bad strategy is course correct frequently every time we see a potential new direction with steeper descent.
The momentum term makes it difficult to course correct frequently by adding weight to the past directions chosen. It dampens (pun intended) the idea of enthusiastically switching directions.
The challenge with common consent: the exact nature of the terrain is going to change from problem to problem (dataset). So your mileage by choosing momentum based updates may vary. But in general, for non-toy problem using momentum based weight updates will be a good first strategy.