Abstract: Music performance analysis has traditionally been a peripheral topic in the music information retrieval community. However, it is sometimes included in the goals of music information retrieval studies—from low- and high-level parameter detection and synchronization methods to feature selection and measure transfer. In this contribution, we introduce the MemoVision software, which utilizes retrieval and feature selection methods for comparative music analysis. It is built with JavaScript and Python languages, combining the accessibility of a web-based interface and state-of-the-art feature extraction possibilities. Its features can be used separately or as a visualization tool for music performance case studies.