async-compare

That's not throughput. You are running exactly 1 promise in parallel at a time and waiting for it to be resolved. However, on node.js you can have more than 1 client served by your server. For instance, your server could have e.g. 10000 promises/callbacks/generators active at a time. Take a look at how different solutions handle that https://github.com/spion/async-compare/blob/master/latest-re.... The results don't change at all if we for example increase latency of I/O by an order of magnitude - that's why latency is not an interesting metric for this use case. It's pretty intuitive, all the 10000 users will just get their results 9ms later but the fact that we could even handle them in the first place without crashing our server matters. ---------- You are right that for your use-case, pretty much the only thing that matters is what imp

Here are some results from my benchmark [1] results for 20000 parallel executions, 1 ms per I/O op file time(ms) memory(MB) promiseishBluebird.js 1076 76.08 async.js 2634 113.79 promiseishKew.js 2654 123.50 promiseishQ.js 56508 804.21 note: async.js is basically waterfall from https://github.com/caolan/async [1]: https://github.com/spion/async-compare