It looks like a competent and thoughtful implementation but, as best I can determine and not to take anything away from it, using an old design. The performance and scalability is throttled by the use of secondary indexing structures. You would have to use some pretty expensive hardware for the performance cliffs to not be immediately evident.

I don’t do a lot of work on graph databases these days, but I’ve seen state-of-the-art implementations do 10x this many inserts/sec/server on EC2 VMs where the local data model size was 100x the available RAM. And in principle these architectures could easily scale-out. Indexing structure and storage engine design figure prominently, both usually need to be built for the purpose.