We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules and decision trees, can be represented and queried using a unifying framework. I. MOTIVATION Data mining is not a one-shot activity, but rather an iterative and interactive process. During the whole discovery process, typically, many different data mining tasks are performed, their results are combined, and possibly used as input for other data mining tasks. To support this knowledge discovery process, there is a need for integrating data mining with data storage and management. The concept of inductive databases (IDB) has been proposed as a means of achieving such integration [1]. In an IDB, one can not only query the data stored in the database, but also the patterns that are implicitly present in these...