A great majority of the effort is spent assembling the data and formulating the features, while, rather ironically, the model building exercise takes relatively less time. beatDB aims at radically shrinking the time of large scale investigations by judiciously pre-computing beat features which are likely to be frequently used. In this paper, we present beatDB structure and use beatDB for a concrete research study: predicting acute hypotensive event with blood pressure.