In the present paper, four kinds of cluster analysis methods were used in rapid, non-destructive discrimination of hypoglycemic tablets by the Raman spectroscopy technology. Nine kinds of hypoglycemic tablets, including 48 samples, were determined using a Raman spectrometer. The sample data were pretreated with the methods of frequency range cutting, baseline correction, smoothing and vector normalization, then were analyzed by K-means, hierachical cluster, self-organizing maps(SOM) and PCA-SOM respectively. The results demonstrated that SOM was better than K-means and hierachical cluster, and it provided the best discrimination when combined with PCA. The research offers a new approach to the rapid discrimination of different kinds of hypoglycemic tablets.