[rcavezza]

Based on my experience, it's the most typically seen bottleneck. But bottlenecks change over time. You notice slowness somewhere in a website action and you dig into it. Sometimes, it's a new database table that isn't optimized with correct indexing. Sometimes, you end up doing an n^2 or n^3 operation on the backend (sometimes it's on the frontend). Sometimes, you're data is growing at a speed that your single monolith database isn't cutting it and you need to shard or consider a different type of storage.

Bottlenecks change all the time. You fix one, and now suddenly, the bottleneck lies somewhere else. There's almost always a bottleneck somewhere. A database bottleneck is relatively common, though.

From my experience, the bottleneck is mostly at some type of Big-O relevant scale in the code or database that using java vs ruby vs python doesn't make a huge difference.

However, if you're in a situation where speed is absolutely crucial - like high frequency trading (where milliseconds mean millions of dollars) - well, that opens a completely different can of worms.

[mandeepj]

Just think about the architecture of NYSE. They are supporting billions of trades per day from so many decades.

[chenster]

And there's Kdb+ https://en.wikipedia.org/wiki/Kdb%2B