Background: Fingerprint analysis and simultaneous multi-components determination are crucial for the holistic quality control of traditional Chinese medicines (TCMs). Yet, reference standards (RS) are often commercially unavailable and with other shortages, which severely impede the application of these technologies. Methods: A digital reference standard (DRS) strategy and the corresponding software called DRS analyzer, which supports chromatographic algorithms, spectrum algorithms, and the combination of these algorithms, was developed. The extensive function also enabled the DRS analyzer to recommend the chromatographic column based on big data.Results: Various quality control methods of fingerprints of 11 compounds in polyphenolic acid extract of Salvia miltiorrhiza (S. miltiorrhiza) were developed based on DRS analyzer, involving relative retention time (RRT) method, linear calibration using two reference substances (LCTRS) technique, RRT combined with Photon Diode Array (PDA) method, LCTRS combined with PDA method. Additionally, the column database of samples was established. Finally, our data demonstrated that the DRS analyzer could accurately identify 11 compounds of the samples, using only one or two physical RSs. Conclusions: The DRS strategy is an automated, intelligent, objective, accurate, eco-friendly, universal, sharing, and promising method for overall quality control of TCMs that requires the usage of fewer RSs.