Performance, scaling and databases

I'm aiming to process a lot of data as quickly as possible, and I'm finding the Postgres connection limit backing my Cayley is being the bottleneck. I started thinking: I can scale up, but maybe there is a bigger issue. It got me wondering about the general performance of Cayley, in particular how it scales with regards to different databases backing it. I looked around a bit and read (skimmed) [this](https://discourse.cayley.io/t/ultimate-direction-for-cayley/160/8).

I feel like it should be doable to set up performance testing with regards to different use-cases and backends. It can be done in fases, general perfomance testing first, backend specific testing later. My first thoughts would be to make use of CircleCI 2.0 here because of its affinity with docker. I'd be happy to help out, although I cannot pledge any time for now. In any case, I'm curious about your thoughts :smiley:.

No files or tests are named. Start by defining the performance use cases and database backends to benchmark, then review the proposed CircleCI 2.0 and Docker approach; done should mean an agreed, repeatable benchmark plan and CI setup, but the issue does not specify concrete success criteria.

Written by the indexing model from the issue text.