An advisor creates configurations for generating multi-representations of time series data based upon detected characteristics such as length, interval, minimums, data types, etc., as well as configurations provided by a user. In an offline mode the advisor may further consider a previous time series workload. In an on-line mode the advisor may adapt multi-representation configurations with respect to ongoing changes in a current time series workload. The advisor may reference a cost model including values quantifying various dimensions (e.g., compression technique, accuracy, covered time period, storage medium, memory consumption, speed) of the multi-representations for optimization purposes. Configurations created by the advisor may be input to a storage engine to generate and store the multi-representations according to goals for data aging, operation execution pattern optimization, and ease of access to time series data located in hot zones. The advisor may be implemented with an engine of an in-memory database.