Cool stuff!

I still always want to know the numbers per edge. Because there'a a reaon why these graph DBs try to hold the stuff in memory, everything else is slow as heck. We have ~30bytes per edge in our succinct indexes, which makes the 1.5gb wiki dataset clock in at ~50gb.

If I understand correctly you shard the graph and then content adress each chunk:

- How do you decide on the sharding? I'd expect finding good connected subsets with nice memory locality to be extremely difficult computationally?

- How do you canonicalise your graph. Which has also been an extremely difficult problem in RDF land for example. Although that one is at least efficiently solvable.