  In this paper we present, by way of case studies, a proof of concept, based
on a prototype working on a automotive data set, aimed at showing the potential
usefulness of using formulas of {\L}ukasiewicz propositional logic to query
databases in a fuzzy way. Our approach distinguishes itself for its stress on
the purely linguistic, contraposed with numeric, formulations of queries. Our
queries are expressed in the pure language of logic, and when we use (integer)
numbers, these stand for shortenings of formulas on the syntactic level, and
serve as linguistic hedges on the semantic one. Our case-study queries aim
first at showing that each numeric-threshold fuzzy query is simulated by a
{\L}ukasiewicz formula. Then they focus on the expressing power of
{\L}ukasiewicz logic which easily allows for updating queries by clauses and
for modifying them through a potentially infinite variety of linguistic hedges
implemented with a uniform syntactic mechanism. Finally we shall hint how,
already at propositional level, {\L}ukasiewicz natural semantics enjoys a
degree of reflection, allowing to write syntactically simple queries that
semantically work as meta-queries weighing the contribution of simpler ones.
