Understood, I did not mean to be overly critical, I just think that there is a lot of misleading information out there concerning graph databases, and for many people it is hard to get good information about their real benefits and drawbacks.
ArangoDB seems to be a very interesting project btw, I might evaluate it again for my project in the future (we are currently creating a very large graph of code data, so we need something that can scale beyond 1B nodes and 100B vertices)
No worries, yes, there is a lot of bad information about graph databases, to begin with, some seem to believe that everything out there can best described by a graph, which is clearly wrong. I have myself written something about this in this article: https://medium.com/@neunhoef/graphs-in-data-modeling-is-the-...
Furthermore, I am currently working on another article for the O'Reilly radar blog presenting a nice case study in which a multi-model database was very useful, because document queries and graph queries were both used extensively.
1B vertices and 100B edges will definitely be a challenge for any graph database and I find it highly likely that ArangoDB in its current version will not show a very good performance for a data set of this size. Obviously, it will always depend on the particular queries you need, and on whether the graph has a natural cluster structure that can be used for sharding.
ArangoDB seems to be a very interesting project btw, I might evaluate it again for my project in the future (we are currently creating a very large graph of code data, so we need something that can scale beyond 1B nodes and 100B vertices)