This benchmark measures the latency of a web service that stores a large (250K item) hashtable, in multiple languages.

Garbage collected languages are of greater interest, and the Swift version is mostly used as a reference of what would be ideal.

• Each HTTP request will add one new item (and remove one if count > 250K)
• Each item will be a new 1KB buffer with every byte initialized to a value.
• Programs will listen on port 8080 and respond with status 200, body "OK"

• All program directories are listed in programs.txt
• Every directory should contain build.sh and run.sh
• wrk2 must be installed and linked in $PATH as wrk2

• Warmup: 9K req/s are sent for 60s (initial hash table content)
• Test : 9K req/s are sent by 99 clients concurrently for 180s

• All reports are in reports directory.
• Charts from both tests can be generated by using hdrhistogram

• go - Go version is go1.6.2 darwin/amd64; uses fasthttp. Using the built-in http library results with a lot more work for the GC, and a chart similar to the one seen for Haskell.
• ocaml-reason - This is built with OCaml 4.03+flambda (ReasonML is currently not compatible with OCaml 4.03 so the ML version was generated from it using refmt first). Follow the instructions here: https://ocaml.org/docs/install.html
• node - Requires node 6.x (Buffer.alloc API)
• haskell - Should build easily if you have stack
• swift-zewo - You should setup swiftenv to the right snapshot

Want to build low-latency, memory-intensive services in a GCed language? Use OCaml (or Reason if you prefer the syntax).

Other things that were attempted to make the latency worse for OCaml:

• random buffer sizes
• longer running time

• simulate extra GC work on a percentage of requests (i.e. creating T temporary objects of size S)