Data processing and analysis has presented major bottlenecks in high-throughput metabolomics research. Bioinformatics tools emerged for performing these high-throughput datasets. These tools can preprocess complex high-dimensional datasets, detect and annotate metabolites, perform various statistical analysis and results interpretation. According to the workflow and methods of metabolomics data processing and analysis, this paper summarized some integral metabolomics softwares and compared the merit and demerit of four typical tools so that it can provide users with a reference guide to softwares.