We propose that modern existential rule reasoners can enable fully declarative implementations of rule-based inference methods in knowledge representation, in the sense that a particular calculus is captured by a fixed set of rules that can be evaluated on varying inputs (encoded as facts). We introduce Datalog (S)–Datalog with support for sets–as a surface language for such translations, and show that it can be captured in a decidable fragment of existential rules. We then implement several known inference methods in Datalog (S), and empirically show that an existing existential rule reasoner can thus be used to solve practical reasoning problems.