With the development of automated planning, the size of problems is getting bigger and bigger, and one can predict that it will become very large in the future. Some existing research work begins to use secondary memories to extend the search space, and it is believed databases are finally used. Besides, many problems that belong to the same domain often have common constants, so there might be a plenty of reusable information to speed up the solution process. To store this information permanently, databases are also needed. Inspired by the above two reasons, this paper first proposes ER (entity relationship) models for PDDL (planning domain description languages) and then develops a stored procedure based automated planner (stored procedure planner, SPP) for the first time. This planner is an optimal one which runs totally inside a database. It stores and accesses data efficiently and takes fully advantages of database features. Experiments on benchmark problems from the Int'l planning competition (IPC) show that this planner can solve problems which cannot be solved by some classical optimal planners in a limited machine configuration. The work in this paper takes the first step for solving planning problems totally in a database so that it is helpful to solve huge-size problems finally.