For the scalability side of graph, we've just started using Amazon Neptune RDF, and have been amazed that we can easily and very quickly run sparql queries on 2.6 billion triples on their smallest 2 core 15 gig machine. Incredible capacity.
Where Neptune appears to fall down is write performance. This is what made it non-viable for me. I have colleagues who are struggling / hacking around the write performance issues.
DGraph's write perf seems to be considerably better - I haven't benchmarked formally, just going off of discussions I've had with others.
As others mention, Neptune is based on Blazegraph. It is a layer on top of Amazon Aurora and has the typical graph layer issues I mention my blog post (in particular the join depth problem).
FYI, Neptune is based on Blazegraph. Amazon's acquisition of Blazegraph halted the database's open development. I'm sure they would welcome interested contributors: https://github.com/blazegraph/database/issues/86
Since Amazon is effectively selling machine time to run Neptune with no cost for the db, wouldn't it be excellent if the original author and team continued to contribute to Blazegraph. I'm not sure if the linked note is a potential nod in that direction or not. (We have customers that also want to have on-prem deployments, which you obviously can't do with Neptune)