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Comment by dnomad | Hacker News Reader

Plenty of people are writing low-latency trading applications in Java where the latency budget is under 100 microseconds. This has been the case for several years now.

It's by no means new or even especially difficult these days. The resulting code is far more maintainable and robust than C++ solutions.

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I've had the opposite experience. For green-field applications, it's far easier to write the application in C++ than Java & meet the latency requirements. Java requires far too much tuning, where as C++, from the get go, you can generally just glance at the code and have a good idea of the latency.

We're currently fighting a Java app that in general has decent latency (10s of usecs), but has outliers of greater than a second when GC kicks in. We don't have that issue with the C++ components of our trading system.

It's always going to be subjective. If you have people experienced in gc tuning, it's pretty easy to weed those gc outliers out. I am currently doing that for one of the applications for the company I work for. For me, it would be far easier to write a low latency, high concurrency Java app than a c++ app. The last c++ app that I was asked to write works horribly and bleeds memory. But it was not an important app.

Oof. There's probably some compounding factors that make it more difficult, but usually getting GC pauses <500ms isn't that hard with current-gen collectors. Either being very careful with CMS, or just feeding G1 a lot of memory.

I’ve heard a pretty effective, lazy strategy for this scenario is to oversize the heap to avoid GCs through the trading day and to simply restart the application before the next day. Unsure if it’s viable for all trading platforms, but it makes sense for some I’m sure.

Depends on your order volume. Sure an oversized heap may work for low order volume, but if you're dealing with high volume, even hundreds of gigabytes of RAM isn't even for a trading day.

And yeah, we restart everyday (we only trade US equities, so plenty of downtime for a restart).

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