What this means is that for your purposes R is fast enough. But in the absolute sense (or in any case, relative to other programming platforms), R is one of the slowest ever. R is usually slower than Python, and Python in some cases can be 100x slower than C.
Performance, assuming identical hardware, depends on the program itself (that is, on what you are trying to calculate or compute or perform), but if you choose many different programs you can have a comparison between platforms ("platform" in this case means combination of programming language plus compiler or interpreter.)
Here is a graphic comparing Julia to other platforms:
https://julialang.org/benchmarks/
You can see that according to that graphic, R can be up to 400x slower than Julia (or C).
There is another independent benchmark here. It does not include R but it includes Python, and it's very interesting.
http://benchmarksgame.alioth.debian.org/
But the best comparison graphs are here, this is worth a look:
http://blog.gmarceau.qc.ca/2009/05/speed-size-and-dependabil...
Performance, assuming identical hardware, depends on the program itself (that is, on what you are trying to calculate or compute or perform), but if you choose many different programs you can have a comparison between platforms ("platform" in this case means combination of programming language plus compiler or interpreter.)
Here is a graphic comparing Julia to other platforms: https://julialang.org/benchmarks/
You can see that according to that graphic, R can be up to 400x slower than Julia (or C).
There is another independent benchmark here. It does not include R but it includes Python, and it's very interesting.
http://benchmarksgame.alioth.debian.org/
But the best comparison graphs are here, this is worth a look: http://blog.gmarceau.qc.ca/2009/05/speed-size-and-dependabil...