<p>This article considers the impact of partitioning large-scale OWL-ontologies (RDF/XML-structures) and parallel query execution on the performance of complex SPARQL queries. The experimental results indicate that ontology partitioning, particularly, for queries with long execution times, can significantly reduce query processing duration. For medium- and long-execution-time queries, a combination of ontology partitioning and parallel execution yields a performance improvement of up to 45% compared to sequential execution. Conversely, for short-execution-time queries, ontology partitioning may introduce additional delays, which can be partially mitigated through parallel processing. In the article, it is also found that partitioning an ontology into more than 7–10 segments does not yield further performance gains, rendering excessive fragmentation an inefficient approach. The article underscores the importance of eliminating redundant constraints in queries, particularly those concerning hierarchical relationships between parent and descendant classes within the ontology. Optimizing or removing these constraints can significantly enhance query execution speed. Furthermore, a formal model is presented to theoretically describe the effects of ontology partitioning and parallel query execution on processing time. Additionally, the article establishes formal criteria for determining the impact of these techniques on different types of queries.</p>