Would you ever need a million open connections? Probably not! But you'll likely want more than 500 at some point. And if your entire stack is serverless already, it'd be nice if the DB could handle that relatively low number of connections too.
Would you ever need a million open connections? Probably not! But you'll likely want more than 500 at some point. And if your entire stack is serverless already, it'd be nice if the DB could handle that relatively low number of connections too.
Even if you have a server with hundreds of cores your database probably can't be actively working on more than a small multiple of the number of the cores.
And previous HN discussion: https://news.ycombinator.com/item?id=32680957.
Modern hardware is totally able to execute hundreds of thousands of transactions per second on a single core. If your query is simple and you can organise getting the data from storage at the necessary speeds you should totally be able to do this many requests, possibly even tens of millions.
But handling one million queries per second is completely different from having database server making progress on one million queries in parallel. What happens is, the database server is only making progress on a small number of them (typically in tens up to hundreds on a very beefy hardware) and everything else is just queued up.
There are much, much better ways to queue up millions of things than opening a million connections to get each one done individually.
We're a DBaaS company, and we do need to be prepared for anything users may throw at us. Our Global Routing infrastructure has seen some major upgrades/changes recently to help support new features like PlanetScale Connect and our serverless drivers.
From our point of view, this was a sizing exercise with the interesting side benefit that many people do happen to use Serverless Functions similarly.
At 46k RPS, it only takes 5.5 ms to assemble a batch of 256, so latency is basically unaffected by doing this. Just set a limit of 5-10 ms to assemble the batch (or lower if you have a more powerful computer that can handle more throughput).