A Knowledge Graph is the data in the database, not the tech.
You can absolutely implement this in a RDBMS. There are some advantages to a proper graph database though.
But SPARQL is a dead-end - I don't think anyone is really using that in practice outside a dew public demonstration apps. To a large extent this is true of RDF too: triples are useful, RDF gets in the way.
We participated in a huge RfP for a pharma company which planned RDF KG infrastructure for the next couple of years with 500 billion triple capabilities.
Biomedical, finance, defence, automotive -- all of those industries are using RDF/SPARQL. Just because your problems are not big or complex enough doesn't mean this tech is not used. It takes a certain organization size for Knowledge Graphs to make sense and pay off, that's why most industry users are Fortune 500-level companies.
You can absolutely implement this in a RDBMS. There are some advantages to a proper graph database though.
But SPARQL is a dead-end - I don't think anyone is really using that in practice outside a dew public demonstration apps. To a large extent this is true of RDF too: triples are useful, RDF gets in the way.