Satellite precipitation estimates with high spatial and temporal resolutions play an important role in near-real-time precipitation monitoring and real-time hydrological forecasting. Four near-real-time satellite precipitation products， including the Fengyun-based （REGC and DISK） and the GPM-based （IMERG-Early and GSMaP-NRT）， were synthesized and analyzed at hourly scales over the Chinese mainland. And the relationships between precipitation inversion errors and four key influencing factors （season， climate zone， rainfall intensity， and topography） were revealed. Results show that： IMERG-Early has the best overall performance with the highest correlation coefficient（CC=0.44） and the lowest root mean square error（RMSE=0.97 mm/h） over the Chinese mainland compared with hourly-scale ground measurements； followed by GSMaP-NRT which performs better and has the lowest false alarm rate in the humid region； while REGC and DISK have satisfactory correlation coefficients and classification statistical indices only in the southern and eastern parts of the humid region. All satellite precipitation estimates performed best in summer and showed poor accuracy in winter. The precipitation intensity analysis shows that the three satellite precipitation products， except IMERG-Early， tend to overestimate the occurrence of rainless events； REGC underestimates the occurrence of light rainfall （0.2~0.6 mm/h） events， but has better agreement with ground measurements and has a lower bias than the other satellite precipitation products. Moreover， DISK has a lower bias in the case of heavy rainfall （>5 mm/h）. Both satellite precipitation products of the GPM series perform better at low altitudes than at high altitudes， while the performance of both precipitation products of FY4A increases significantly at high altitudes （DEM>3 000 m）. The evaluation results related here will provide some valuable feedback to the algorithm developers of the Fengyun products and enable data users to further understand the error characteristics and potential shortcomings of the Fenyun precipitation estimates.