We present the GeoRDFBench framework, whose purpose is to assist and streamline the benchmarking of geospatial semantic stores. We identify and formally define all benchmark components, extend them to represent their geospatial aspects, allow for the automatic mapping of datasets to graphs, provide a specialization hierarchy of queryset types for micro or macro experimental scenarios, even for modeling dynamically generated queries. Queries may define their expected resultset to enable automatic accuracy verification. Experiment behavior and execution logic is controlled by the execution specification, which dictates the action (run experiment or print ground queries) to take, the number of repetitions per execution type (cold, warm, continuous cold), the query repetition and experiment timeouts, the delay period before clearing caches, the aggregating function for reporting execution times, and the policy to follow upon cold execution time out. We decouple these declarative benchmark specifications from the framework's execution engine and serialize them as JSON files; this way, we increase their reuse (instantiation through deserialization), experiment reproducibility and dissemination. We also model the Geospatial RDF store optional application and database server modules and manage their life-cycle (start, stop, restart) during experiment execution to achieve ideal cold cache query executions. In addition, we unify by generalization the repository and connection functionalities of the three most common RDF framework Java APIs offered by RDF stores: OpenRDF Sesame, Eclipse RDF4J and Apache Jena. At the same time GeoRDFBench allows queryset filtering, automatic system-dependent query namespace prefix generation and query rewriting when non GeoSPARQL spatial vocabularies are used. We provide for a quick learning start by implementing several geospatial RDF stores as separate runtime-dependent modules with repository generation and experiment execution scripts. RDF modules include: RDF4J with and without Lucene, GraphDB, Stardog, Strabon, OpenLink Virtuoso and Jena GeoSPARQL.