Python's csv module uses an internal module _csv which is written in C. So I'm not sure it's all that surprising that a Go implementation is a bit slower.
I run the benchmark using PyPy (which doesn't have this C extension) and got a result about 20% slower compared to CPython (ie. still faster than Go).
EDIT. I also did a funny thing and replaced the CPython C _csv.so extensions with pure Python version _csv.py, from PyPy. It run about 80 (eighty) times slower. It shows what wonders does JIT do (at least to some code).
I thought it is rather part of the solution/answer to the issue. It is expected to be slower, so it's not necessarily broken. Kind of it's a feature, not a bug.
There's a performance cost to calling between c and Go, and sharing memory between the two makes for hard to predict GC behavior. I doubt it would be faster than a pure Go implementation.
There's nothing mysterious about the Java version... that's not a CSV parser. The other two things are truly CSV parsers. (Inasmuch as there is such a thing for such an ill-defined format. (No, the RFC is not determinative.))
It's easy to be faster if you do fundamentally less. Not necessarily wrong, depending on your task, but it's not comparable.
The Java code is defective. It's not checking for double quotes. The CSV format allows for commas inside column values by surrounding with double quotes, and then you can also put double quotes within such values by escaping them as double double quotes. Fix those defects and the Java code will be a little slower.
With modern JVMs, Java can occasionally actually be faster than native compiled languages due to dynamic optimization at runtime.
actually the java one is still amazing since it's a cold jvm.
when it would be a big file I would think that java is far ahead of both. with an aggressive jit.
maybe pypy is faster than all 3 :D
Besides the point that the Java example is not a good one; The JVM is actually a pretty mean piece of software with a lot of optimisation. So while Go could in theory produce faster code then Java I doubt the Go compiler is clever enough to produce faster code then the JVM in a lot scenarios (at the moment).
But Java conceptually has a lot of drawbacks that require the JVM to have screaming performance to compensate for. Almost everything being a "headered" object being probably the worst offender. Even a slightly worse Go compiler is probably well compensated-for by denser data structure layout in the operating memory.
Only true until value types get productified and there are already prototype versions to play with.
Also depending on which JVM SDK is being used (Oracle Hotspot, Oracle Graal, IBM J9, HP, PTG, JET,...), the quality of escape analysis differs but it all boils down to turning those headered objects into plain structs, if possible stack allocated.
In what sense is an articulated object a "conceptual drawback"? It is a richer object model and SMI and friends had the engineering chops to makes it highly performant.
If you want an actual rich object model, why aren't you using CLOS instead? Java's objects costs you a lot of potential performance with few of the benefits.
EDIT. I also did a funny thing and replaced the CPython C _csv.so extensions with pure Python version _csv.py, from PyPy. It run about 80 (eighty) times slower. It shows what wonders does JIT do (at least to some code).