During the last decade, a lot of algorithms have been developed for mining frequent several types of patterns in several types of databases. Nevertheless, a system that can efficiently mine patterns in an arbitrary relational database is still nonexistent. Inspired by the work done in ILP, we further explore the opportunity of mining conjunctive queries. Conjunctive query evaluation in relational databases is well understood, but still poses some great challenges when approached from a discovery viewpoint in which patterns are generated and evaluated with respect to some well defined search space and pruning operators. In this presentation, we propose an efficient algorithm to mine queries belonging to a very small and simple subclass of conjunctive queries, and show that still a lot of interesting patterns can be expressed as such.