In addition to labelled property graphs and triples, a list of approaches to knowledge graph should consider facts(tuples) that are connected via common values

In addition to labelled property graphs and triples, a list of approaches to knowledge graph should consider facts(tuples) that are connected via common values as a form of graph, with datalog queries to query them. This is a lot more flexible than either approach IMHO and also more easily connected to existing relational data. RDFox is a tool that uses Datalog internally. RelationalAI uses a datalog based approach. Another example is Mangle Datalog, my own humble open source project that can be found on GitHub. The language in the article about relational being "non native graph" is a bit biased. With some developer attention, there are massive opportunities to store data in a distributed manner and with te right indices querying can be fast. Though to be fair, good performance will always need developer attention.