The main objective of this study is to validate and inter-compare two Near-Real-Time Satellite Rainfall Estimates (NRT-SREs): INSAT Multispectral Rainfall Algorithm (IMSRA, simple blended product) and TMPA 3B42-RT V7 (3B42-RT, multisatellite product) across India. This study aims to provide some insight into the error characteristics of both the NRT-SREs to the algorithm developers and end users by inter-comparing the daily rainfall estimates during the southwest monsoon period of 2010–2013. This study utilizes various volumetric statistics and categorical statistics to understand and evaluate the performance of NRT-SREs in terms of both spatial and volumetric error characteristics (hit, miss, and false error) at different rainfall thresholds across different Köppen–Geiger climate regions of India using the gridded gauge data provided by Indian Meteorological Department as reference dataset. A detailed statistical evaluation shows that the 3B42-RT performs comparatively better than the IMSRA across India. The results indicate that both IMSRA and 3B42-RT have a general tendency of overestimating the low rainfall rates (0–2.5 mm/day) and underestimating the high rainfall rates (> 35.5 mm/day). At lower threshold values (0 and 2.5 mm/day), it is found that the miss error is dominant in IMSRA, whereas the false error is dominant in 3B42-RT. As the threshold increases (7.5 and 35.5 mm/day), both the miss and false errors increase in both SREs. Additionally, the spatial analysis of the results clearly indicate that the performance of the tested NRT-SREs is not uniform across different climatic regions, an important aspect to be considered for development/improvement of the tested NRT-SRE algorithms. © 2017, Springer International Publishing AG, part of Springer Nature.