FSQL and SQLf: Towards a Standard in Fuzzy Databases

In order to give greater flexibility to relational dababase management systems (RDBMS), different languages and models have been conceived with the incorporation of fuzzy logic concepts into information treatment. Two outstanding proposals in fuzzy logic application to databases are those of FSQL (Galindo, 1999, 2007) and SQLf (Bosc & Pivert, 1995a). This chapter shows a comparison on these two applications from different points of view. FSQL was created in order to allow the treatment of the uncertainty in fuzzy RDBMS. It allows the representation and manipulation of precise and vague data. It distinguishes three data categories: crisp, referential ordered, and referential not ordered. It uses possibility distributions and similarity relations for the representation of vague data, using the model GEFRED (Medina, 1994; Medina, Pons, & Vila, 1994). For the manipulation of these data, FSQL extends some components of SQL with elements of fuzzy logic. It includes the use of possibility and necessity measures. Surroundings to AbstrAct