This work focuses on improving a density-based algorithm called Bridge Aware Clustering in terms of scalability, cluster fragmentation robustenss and noise ro-bustness. The scalability improvements were conducted by implementing a distributed version of Bridge Aware Clustering on Spark using Python.The cluster fragmentation robustness improvements were conducted by integrating a cluster fusion technique documented in the literature and testing it over different benchmark datasets. The noise robustness improvements were conducted by integrating a noise detection method through an extensive testing campaign aiming to evaluate the noise robustness over different levels of noise.