This article introduces TanaT, an open-source framework for temporal sequences analysis. Temporal sequences are made of complex events, described by qualitative and quantitative features, with a contiguous temporal footprint. Such kind of data are encountered in a wide range of applications (medicine, social science, traces analysis, education, etc.) and their analysis requires taking into account the longitudinality of the data. The proposed framework aims to empower data analysts with a coherent toolbox for handling such temporal sequences at all stages of the analysis process: data loading, data pre-processing and transformation, data analysis and data visualization. In this article, we introduce our framework, focusing on the distance-based clustering of temporal sequences. The complex nature of temporal entities requires versatility in defining distances between sequences and we highlight how TanaT addresses this challenge https://gitlab.inria.fr/tanat/core/tanat .