Abstract. The concept of preference-aware processing is dominant in many applications, such as personalized search and recommendations. Still, it is implemented in a piecemeal fashion and typically outside the query engine. In this work, we present a preference-aware relational data model that extends database tuples with preferences and an extended algebra that captures the essence of preference-aware processing. The key novelty of our preference model itself is that it allows defining a preference in a 3-dimensional way, where the conditional dimension specifies the tuples affected, the ranking one describes how they are affected (i.e., scored) and the confidence dimension captures the credibility of the preference. Our approach allows us to freely combine preferences into queries. We describe several examples of preference-aware queries and we present techniques for efficient query evaluation on top of a conventional relational database. Our experimental results using our prototype implementation show the efficiency and potential of our approach.