web-benchmarks VS Disruptor

If your team is familiar with Node, you can use it to write high performance servers that perform at almost the same level as Go or Java: https://github.com/nDmitry/web-benchmarks. It’d probably be worth learning how to benchmark and profile your current services too. It will require choosing your libraries carefully for high performance and being thoughtful about loops and allocations, but you would need to do that with Go and Java too.

https://lmax-exchange.github.io/disruptor/#_what_is_the_disr.... Unfortunately IIUC writing this in Go still prevents the spin-locked acceptor thread from achieving the kind of performance you could get in a non-GC language, unless you chose to disable GC, so I'd guess Envoy is still faster.

https://gnet.host/docs/quickstart/ it's nice that you can use this simply though. Envoy is kind of tricky to setup with custom filters, so most of the time it's just a standalone binary.

[0] https://blog.envoyproxy.io/envoy-threading-model-a8d44b92231...

[1] https://lmax-exchange.github.io/disruptor/#_what_is_the_disr...

See also the Java LMAX Disruptor https://github.com/LMAX-Exchange/disruptor

I've built a similar lock-free ring buffer in C++11 https://github.com/posterior/loom/blob/master/doc/adapting.m...

"Why we chose Java for our High-Frequency Trading application"

https://medium.com/@jadsarmo/why-we-chose-java-for-our-high-...

LMAX Disruptor customers

https://lmax-exchange.github.io/disruptor/

Among many other examples.

Current documentation

https://lmax-exchange.github.io/disruptor/

LMAX Disruptor has on their wiki that average latency to send a message from one thread to another at 53 nanoseconds. For comparison a mutex is like 25 nanoseconds and more if Contended but a mutex is point to point synchronization.

The great thing about it is that multiple threads can receive the same message without much more effort.

https://github.com/LMAX-Exchange/disruptor/wiki/Performance-...

https://gist.github.com/rmacy/2879257

I am dreaming of language that is similar to Smalltalk that stays single threaded until it makes sense to parallise.

I am looking for problems to parallelism that are not big data. Parallelism is like adding more cars to the road rather than increasing the speed of the car. But what does a desktop or mobile user need to do locally that could take advantage of the mathematical power of a computer? I'm still searching.

Database config should be two connection strings, 1 for the admin user that creates the tables and anther for the queue user. Everything else should be stored in the database itself. Each queue should be in its own set of tables. Large blobs may or may not be referenced to an external file.

Shouldn't a message send be worst case a CAS. It really seems like all the work around garbage collection would have some use for in-memory high speed queues.

Are you familiar with the LMAX Disruptor? Is is a Java based cross thread messaging library used for day trading applications.

https://lmax-exchange.github.io/disruptor/

Disruptor for inter-thread messaging

I have never worked in any industries where a perf margin was that small. It is funny, in HFT there are folks using Lmax (Java) and then you have folks writing their own TCP/IP stacks on FPGAs to do trading.