Very fast SPARQL Engine, which can handle very large knowledge graphs like the complete Wikidata, offers context-sensitive autocompletion for SPARQL queries, and allows combination with text search. It's faster than engines like Blazegraph or Virtuoso, especially for queries involving large result sets.
It would be nice to be able to write non-federated queries but have them run automatically as federated queries over a union of multiple QLever endpoints. This way, the queries would be simpler to write and would require less knowledge.
I have no idea about the scalability issues but perhaps you have already investigated this? If full automation is not feasible, perhaps there would still be an easier interface than the current SERVICE functionality (where you need to split the query based on where each triple is stored).
Use cases: Wikidata + SDC, Wikidata + OSM, (Wikidata - scholarly articles) + (scholarly articles) etc.
It would be nice to be able to write non-federated queries but have them run automatically as federated queries over a union of multiple QLever endpoints. This way, the queries would be simpler to write and would require less knowledge.
I have no idea about the scalability issues but perhaps you have already investigated this? If full automation is not feasible, perhaps there would still be an easier interface than the current SERVICE functionality (where you need to split the query based on where each triple is stored).
Use cases: Wikidata + SDC, Wikidata + OSM, (Wikidata - scholarly articles) + (scholarly articles) etc.