In this work, we demonstrate how to setup a Wikidata SPARQL endpoint on commodity hardware resources. We achieve this by using a novel triple store called qEndpoint, which uses a read-only partition based on HDT and a write partition based on RDF4J. We show that qEndpoint can index and query the entire Wikidata dump (currently 17 billion triples) on a machine with 600GB SSD, 10 cores and 10GB of RAM, while keeping the query performance comparable with other SPARQL endpoints indexing Wikidata. In a nutshell, we present the first SPARQL endpoint over Wikidata that can run on commodity hardware while preserving the query run time of existing implementations. Our work goes in the direction of democratizing the access to Wikidata as well as to other large-scale Knowledge Graphs published on the Web. The source code of qEndpoint along with the query workloads are publicly available. CCS CONCEPTS • Information systems → DBMS engine architectures.