Then why is it that IO-heavy benchmarks such as the Techempower web benchmark are dominated by async frameworks? The fastest results there are all from async frameworks [1].
And among Rust frameworks the same pattern holds. The fastest Rust frameworks are async while a synchronous frmework such as Rocket is about 20x slower.
> A context switch takes around 0.2µs between async tasks, versus 1.7µs between kernel threads. But this advantage goes away if the context switch is due to I/O readiness: both converge to 1.7µs.
This is a big surprise.
If you look at the Techempower web benchmark [1], the performance of actix-web is about 20x higher than that of Rocket.
The common explanation is that actix-web is async and hence much faster than Rocket which relies on kernel context switching.
But if Rust async and kernel thread has the same switch time as shown by this benchmark, then why is actix-web so much faster than Rocket?
How does Rust async compare to Goroutine, Erlang threads, Javascript async, Java async in performance and memory usage? Is there any benchmarks for that?
I remember reading about this a few years ago here. If I remember correctly back then the main selling point was that it used succinct data structure and it was only the compression algo that was not open source - everything else was.
But now when I look at the new repo and the online doc there is no mention of succinct data struct anywhere.
Also, the benchmarks back then claimed 10x or more faster than RocksDB. Now the performance claim is much more modest.
Does that mean TerarkDB no longer uses succinct data struct? Or are you just open sourcing a lower-end version of the software without the secret sauce?
Can you talk about what makes TerarkDB faster than RocksDB?
You can easily buy a machine with several TB of RAM, several hundreds of TB of SSDs in RAID giving you millions of IOPS, quad-socket 256 cores. How likely is it that a single machine cannot handle a single customer?
While it sounds nice in theory, in practice it was very slow. The only thing TokuDB good at was bulk inserts. Other than that both writes and reads were slower than B+ tree.
I think eventually TokuDB just faded away.
Is there any other implementation of COLA/Fractal Tree that fares better?
So it takes $22 million investment to add just 1 job?
Something seems off.