Applications ranging from algorithmic trading to scientific data analysis require realtime analytics based on views over databases that change at very high rates. Such views have to be kept fresh at low maintenance cost and latencies. At the same time, these views have to support classical SQL, rather than window semantics, to enable applications that combine current with aged or historical data. In this paper, the authors present viewlet transforms, a recursive finite differencing technique applied to queries. The viewlet transform materializes a query and a set of its higher-order deltas as views.