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From a purely photometric perspective galaxies are generally decomposed intoa bulge+disc system, with bulges being dispersion-dominated and discsrotationally-supported. However, recent observations have demonstrated thatsuch a framework oversimplifies complexity, especially if one considers galaxykinematics. To address this issue we introduced with the GPU-based code\textsc{bang} a novel approach that employs analytical potential-density pairsas galactic components, allowing for a computationally fast, still reliable fitof the morphological and kinematic properties of galaxies. Here we apply\textsc{bang} to the SDSS-MaNGA survey, estimating key parameters such as mass,radial extensions, and dynamics, for both bulges and discs of +10,000 objects.We test our methodology against a smaller subsample of galaxies independentlyanalysed with an orbit-based algorithm, finding agreement in the recoveredtotal stellar mass. We also manage to reproduce well-established scalingrelations, demonstrating how proper dynamical modelling can result in tightercorrelations and provide corrections to standard approaches. Finally, wepropose a more general way of decomposing galaxies into "hot" and "cold"components, showing a correlation with orbit-based approaches and visuallydetermined morphological type. Unexpected tails in the "hot-to-total"mass-ratio distribution are present for galaxies of all morphologies, possiblydue to visual morphology misclassifications.

Decomposing galaxies with BANG: an automated morpho-kinematical decomposition of the SDSS-DR17 MaNGA survey