Abstract: Time series forecasting is crucial in a number of domains such as production planning and energy load balancing. In these areas, forecasts are often required by non-expert users on large multi-dimensional data sets expecting short response times. However, as current traditional database systems support forecasting only in a limited and non-declarative way, it is performed outside the database system by specially trained experts. We introduce a novel approach that seamlessly integrates time series forecasting into an existing database management system. In contrast to flash-back queries that allow a view on the data in the past, we have developed a Flash-Forward Database System (F2 DB) that provides a view on the data in the future. It supports a new query type — a forecast query — that enables forecasting of time series data for any user and is automatically processed by the core engine of an existing DBMS. We introduce various optimization techniques for three different...