Reanalysis products represent a valuable source of information for different impact modelling and monitoring activities over regions with sparse observational data. It is therefore essential to evaluate their behavior and their intrinsic uncertainties. In this study, we focus on precipitation over monsoon Asia, a key agricultural region of the world. Four reanalysis datasets are evaluated, namely ERA-Interim, ERA-Interim/Land, AgMerra and JRA-55. APHRODITE and CHIRPS are two gridded observational datasets, the latter is based on rain gauge, and the former on satellite/rain gauge data. Differences in seasonality, moderate-to-heavy precipitation events, daily distribution and drought characteristics are analyzed. Results show remarkable differences between the APHRODITE and CHIRPS observational datasets as well as between these datasets and the reanalyses. AgMerra generally achieves the best performance, but it is not a near real time updated dataset. ERA-ILand shows good spatial performance, but when the interest is on the temporal evolution, JRA-55 is recommended, as it exhibits the most stable temporal behavior. This study shows that the use of reanalyses for impact modelling and monitoring over monsoon Asia requires an accurate evaluation and choices to be tailored to the specific needs.