Plan enumeration is one of the most crucial components in relational query optimization. We demonstrate RLQDAG, a system implementation of a top-down plan enumerator for the purpose of transforming sets of recursive relational terms efficiently. We describe a complete system of query optimization with parsers and compilers adapted for recursive queries over knowledge and property graphs. We focus on the enumeration component of this sytem, the RLQDAG, and especially on its efficiency in generating plans out of reach of other approaches. We show graphical representations of explored plan spaces for queries on real datasets. We demonstrate the plan enumerator and its benefits in finding more efficient query plans.