Neural Graph Databases. A new milestone in graph data…

Vanilla graph databases are pretty much everywhere thanks to the ever-growing graphs in production, flexible graph data models, and expressive query languages. Query engines assume that graphs in classical graph DBs are complete. Under the completeness assumption, we can build indexes, store the graphs in a variety of read/write-optimized formats and expect the DB would return what is there. But this assumption does not often hold in practice (we'd say, doesn't hold way too often). If we look at some prominent knowledge graphs (KGs): in Freebase, 93.8% of people have no place of birth and 78.5% have no nationality, about 68% of people do not have any profession, while in Wikidata, about 50% of artists have no date of birth, and only 0.4% of known buildings have information about height.