  Feature model configuration can be supported on the basis of various types of
reasoning approaches. Examples thereof are SAT solving, constraint solving, and
answer set programming (ASP). Using these approaches requires technical
expertise of how to define and solve the underlying configuration problem. In
this paper, we show how to apply conjunctive queries typically supported by
today's relational database systems to solve constraint satisfaction problems
(CSP) and -- more specifically -- feature model configuration tasks. This
approach allows the application of a wide-spread database technology to solve
configuration tasks and also allows for new algorithmic approaches when it
comes to the identification and resolution of inconsistencies.
