We address the issue of Ontology-Based Query Answering (OBQA), which seeks to exploit knowledge expressed in ontologies when querying data. Ontologies are represented in the framework of ex-istential rules (aka Datalog±). A commonly used technique consists in rewriting queries into unions of conjunctive queries (UCQs). However, the obtained queries can be prohibitively large in practice. A well-known source of combinatorial explosion are very simple rules, typically expressing taxonomies and relation signatures. We propose a rewriting technique, which consists in compiling these rules into a preorder on atoms and embedding this preorder into the rewriting process. This allows to compute compact rewritings that can be considered as " pivotal " representations, in the sense that they can be evaluated by different kinds of database systems. The provided algorithm computes a sound, complete and minimal UCQ rewriting , if one exists. Experiments show that this technique leads to substantial gains, in terms of size and runtime, and scales on very large ontologies. We also compare to other tools for OBQA with existen-tial rules and related lightweight description logics.