Comparative hydrology has been found to deepen our understanding of hydrological processes in catchments and helps to improve the proper evaluation of hydrological models. Recently, the global hydrological community has developed a series of publicly available, large-scale CAMELS-datasets that provide catchment attributes and meteorological time series of catchments on a national level. These datasets include catchment-averaged values of catchment characteristics and meteorological time series and therefore allow only lumped modeling. In this study, we introduce a new dataset "CAMELS-SAX" for large-sample studies in the region of Saxony (Germany), which has a high diversity and heterogeneity of catchment attributes, such as geology and land use. "CAMELS-SAX" consists of meteorological and hydrological time series covering 60 years of data on a daily timestep for more than 200 catchments. The dataset includes spatially distributed catchment attributes and covers an area of about 23.000 km² with undisturbed and anthropogenic-influenced catchments ranging from 1 km² up to 5.000 km², which can be used for spatially distributed modelling. We will provide the standardized dataset for the German Federal State of Saxony for studies evaluating distributed models' performance on a smaller spatial scale. In the presentation, we show an overview of catchment attributes, time series, and hydrological signatures for the subset of undisturbed catchments. In addition, we present the results of a sensitivity analysis of the hydrological behavior caused by climate change.