This paper investigates the use of graph rewriting rules to model updates-instance or schema changes-on RDF/S databases which are expected to satisfy RDF intrinsic semantic constraints. Such databases being modeled as knowledge graphs, we propose graph rewriting rules formalizing atomic updates whose application transforms the graph and necessarily preserves its consistency. If an update has to be applied when the application conditions of the corresponding rule do not hold, side-effects are generated: they engender new updates in order to ensure the rule applicability. Our system, SetUp, implements our updating approach for RDF/S data and offers a theoretical and applied framework for ensuring consistency when a RDF knowledge graph evolves.