Inferential statistics teach us that we need a random probability sample to infer from a sample to the general population. In online survey research, however, volunteer access panels, in which respondents self-select themselves into the sample, dominate the landscape. Such panels are attractive, due to their low costs. Nevertheless, recent years have seen increasing numbers of debates about the quality, in particular about errors in the representativeness and measurement, of such panels (Baker et al., 2010). In this paper, we describe four probability-based online and mixed-mode panels for the general population: the LISS Panel in the Netherlands, the German Internet Panel and the GESIS Panel in Germany, and the ELIPSS Panel in France. We compare them in terms of sampling strategies, offline recruitment procedures, and panel characteristics. Our aim is to provide an overview to the scientific community of the availability of such data sources, to demonstrate to practitioners potential strategies for recruiting and maintaining probability-based online panels, and to direct analysts of the comparative data collected across these panels to methodological differences that may affect comparative estimates.