Identification and quantification of small RNAs are challenging because of their short length, high sequence similarities within microRNA (miRNA) families, and the existence of miRNA isoforms and O-methyl 3' modifications. In this study, the detection performance of three high-throughput commercial platforms, Agilent and Affymetrix microarrays and Illumina next-generation sequencing, was systematically and comprehensively compared. The ability to detect miRNAs was shown to depend strongly on the platform and on miRNA modifications and sequence. Using synthetic transcripts, including mature, precursor, and O-methyl-modified miRNAs spiked into human RNA, a large intensity variation in all spiked-in miRNAs and a reduced capacity in detecting O-methyl-modified miRNAs were observed between the tested platforms. In addition, endogenous human miRNA expression levels were assessed across the platforms. Detected miRNA expression levels were not consistent between platforms. Although biases in miRNA detection were previously described, here the end-point result, i.e., detection intensity, of these biases was investigated on multiple platforms in a controlled fashion. A detailed exploration of a large number of attributes, including base composition, sequence structure, and isoform miRNA attributes, suggests their impact on miRNA expression detection level. This study provides a basis for understanding the attributes that should be considered to adjust platform-dependent detection biases.