The question of large scale data architecture is of course a vast topic and I am far from an expert. However, I am interested in how JSON-LD is used at scale, so please excuse the lack of specificity and the high-level question.
Clearly, big players like Google incorporate JSON-LD for example in Google Knowledge Graph.
Taking this as an example, supposing that JSON-LD is used as data format for I/O in the Knowledge Graph, how is the data base build so it is possible to query such masses of data? Is it reliant on translating to RDF-triples for querying with SPARQL, or are there other architectures that makes data queryable in raw JSON-LD format? What are the tricks, if any, enabling the processing (and querying) of JSON-LD at large scale?
Systems like MongoDB or Virtuoso(?) are useful for managing large JSON-formatted data and making it queryable, but is it ever desirable to specify JSON(-LD) as a back-end format for data rather than, say, xml (if one wishes to use some sort of RDF)?
Again, apologies for the vagueness. Any inputs, such as general pointers or discussion on the topic will be much appreciated.