GLENDA: Querying over RDF Archives with SPARQL


The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of a large RDF dataset accessible. That said, existing archiving techniques fail to scale when confronted to very large RDF archives and complex SPARQL queries. GLENDA is a system capable of running full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration fast SPARQL query processing over multiple versions is possible. Moreover GLENDA provides different statistics about the history of RDF datasets. This provides insights about the evolution dynamics of the data.


GLENDA is a system permitting archiving and querying of large, dynamic semantic datasets. Unlike existing techniques, GLENDA is able to handle large RDF datasets while supporting complex SPARQL 1.1 queries. GLENDA makes use of OSTRICH, an hybrid RDF Archives indexing system which combines multiple-snapshots and delta-chains to efficiently capture and preserve the complete history of RDF datasets. With GLENDA, users can execute sophisticated version queries, leveraging the full capabilities of SPARQL 1.1 across multiple graph versions. This empowers researchers and developers to gain comprehensive insights into the data's transformation over its lifespan. Beyond querying, GLENDA also offers visually informative statistics about the dataset's history, providing valuable insights into the dynamics of its evolution.

GLENDA was presented at ESWC 2023 and was awarded the best demo award.


A demo website setup with GLENDA can be accessed at

You can find our paper here.

The code of the demo system along with instructions to setup and run it are available on GitHub under the MIT licence.