Neo4j, a graph database management system, is capable of loading and writing RDF data. However, until now, RDF and OWL reasoning have been associated with fully-fledged triple stores or dedicated reasoning engines only. This post demonstrates that Neo4j can be extended by a unique reasoning technology to deliver an expressive and competitive reasoning engine for RDF, RDFS, and OWL 2 RL. The approach leverages labeled property graphs and the Resource Description Framework (RDF), which consider data as a graph. Neo4j's node labels can encode lightweight type schemas, while RDF Schema (RDFS) structures labels in hierarchies, and the Web Ontology Language (OWL) provides rule-like conditions to automatically derive new facts. GraphScale, a technology that empowers Neo4j with scalable OWL reasoning, uses abstraction refinement to build a compact representation of the graph suitable for in-memory reasoning. This approach has been shown to be sound and complete for all of RDF, RDFS, and OWL 2 RL, and it provides a competitive query performance with the previous datasets. The integration of Neo4j and GraphScale enables a transactional graph analytics system as well as a RDFS/OWL reasoning engine, which can service sophisticated semantic applications via Cypher over a materialized graph in Neo4j.