[lmeyerov]

Separate benchmark per claim and core use case :) A scale-to-zero + autoscaling graph db could be both broadly relevant and differentiated, so I'd be curious there + table stakes for regular queries.

RE:extremes, we see graph DBs OK for small time series (ex: 2 nodes with a bunch of event multiedges), but not full blown time series... where we'd use a tsdb. Some vendors demo this, but always felt like wrong tool.

The many-hop case is interesting! We don't see 1K-hops typically, and I get nervous even at 10-20 on graph DBs we've used. I can imagine in logistics or sciences that happening more, or maybe even some rdf systems. Partition keys start mattering fast, whether a kvdb or a mpp, but I don't have an intuition here. Probably easier to differentiate on, but too niche?

[skafoi]

Thanks for your input.

1k hops is also not something we see on a regular basis in our old business, which is much about people moving houses and transactional data from payment service providers. Ppl with money issues seem to move a lot more often and also fraud cases often have a lot of hops.