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TechEmpower
FrameworkBenchmarks
C++2013–2026
TechEmpower / FrameworkBenchmarks · Archived

FrameworkBenchmarks

Source for the TechEmpower Framework Benchmarks project

Testing & Quality
Explore on GitHubRead Hacker News discussions
143Distinct people
247Mentions
3Explicit recommenders
8.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Source for the TechEmpower Framework Benchmarks project

GitHub

Where it is used

  • ASP.NET Core — ASP.NET Core used the TechEmpower Framework Benchmarks as a focus for performance work. Microsoft prioritized improving ASP.NET’s performance in these benchmarks. Source
  • Benchmarks for ASP.NET Core — Benchmarks for ASP.NET Core includes scenarios from the TechEmpower Web Framework Benchmarks in its benchmarking suite. Source

What people are saying

Sorry, I should have been more precise. I am very, very familiar with the TechEmpower benchmarks and I first learned Java around SE 5, right after they switched from 1.x…

AaronFriel used a recommendation phrase. 3 indexed comments match. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 1:57:11 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year247 dated mentions

Observed mentions: 2013-03-28 15:05:31 UTC to 2026-03-24 12:37:38 UTC.

02550751002013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 106 mentions; 2 submissions, 104 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 20 mentions; 0 submissions, 20 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 9 mentions; 0 submissions, 9 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 10 mentions; 0 submissions, 10 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 14 mentions; 0 submissions, 14 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 25 mentions; 0 submissions, 25 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 14 mentions; 0 submissions, 14 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 15 mentions; 0 submissions, 15 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 8 mentions; 1 submissions, 7 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 4 mentions; 2 submissions, 2 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC1062104
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC20020
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC808
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC808
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC404
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC909
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC10010
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC14014
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC25025
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC14014
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC15015
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC817
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC422

From the project README

An excerpt from the repository, fetched Nov 13, 2026.

Read the project’s introduction
Welcome to TechEmpower Framework Benchmarks (TFB) If you're new to the project, welcome! Please feel free to ask questions here. We encourage new frameworks and contributors to ask questions. We're here to help! This project provides representative performance measures across a wide field of web application frameworks. With much help from the community, coverage is quite broad and we are happy to broaden it further with contributions. The project presently includes frameworks on many languages including Go, Python, Java, Ruby, PHP, C#, F#,Clojure, Groovy, Dart, JavaScript, Erlang, Haskell, Scala, Perl, Lua, C, and others. The current tests exercise plaintext responses, JSON serialization, database reads and writes via the object-relational mapper (ORM), collections, sorting, server-side templates, and XSS counter-measures. Future tests will exercise other components and greater computation. Read more and see the results of our tests on cloud and physical hardware. For descriptions of the test types that we run, see the test requirements section. If you find yourself in a directory or file that you're not sure what the purpose is, checkout our file structure in our documentation, which will briefly explain the use of relevant directories and files. Quick Start Guide To get started developing you'll need to install docker or see our Quick Start Guide using vagrant Clone TFB. $ git clone https://github.com/TechEmpower/FrameworkBenchmarks.git Change directories $ cd FrameworkBenchmarks Run a test. $ ./tfb --mode verify --test gemini Explanation of the ./tfb script The run script is pretty wordy, but each and every flag is required. If you are using windows, either adapt the docker command at the end of the ./tfb shell script (replacing ${SCRIPT_ROOT} with /c/path/to/FrameworkBenchmarks), or use vagrant. The command looks like this: docker run -it --rm --network tfb -v /var/run/docker.sock:/var/run/docker.sock -v [FWROOT]:/FrameworkBenchmarks techempower/tfb [ARGS] -it tells docker to run this in 'interactive' mode and simulate a TTY, so that ctrl+c is propagated. --rm tells docker to remove the container as soon as the toolset finishes running, meaning there aren't hundreds of stopped containers lying around. --network=tfb tells the container to join the 'tfb' Docker virtual network The first -v specifies which Docker socket path to mount as a volume in the running container. This allows docker commands run inside this container to use the host container's docker to create/run/stop/remove containers. The second -v mounts the FrameworkBenchmarks source directory as a volume to share with the container so that rebuilding the toolset image is unnecessary and any changes you make on the host system are available in the running toolset container. techempower/tfb is the name of toolset container to run A note on Windows Docker expects Linux-style paths. If you cloned on your C:\ drive, then [ABS PATH TO THIS DIR] would be /c/FrameworkBenchmarks. Docker for Windows understands /var/run/docker.sock even though that is not a valid path on Windows, but only when using Linux containers (it doesn't work with Windows containers and LCOW). Docker Toolbox may not understand /var/run/docker.sock, even when using Linux containers - use at your own risk. Quick Start Guide (Vagrant) Get started developing quickly by utilizing vagrant with TFB. Git, Virtualbox and vagrant are required. Clone TFB. $ git clone https://github.com/TechEmpower/FrameworkBenchmarks.git Change directories $ cd FrameworkBenchmarks/deployment/vagrant Build the vagrant virtual machine $ vagrant up Run a test $ vagrant ssh $ tfb --mode verify --test gemini Add a New Test Either on your computer, or once you open an SSH connection to your vagrant box, start the new test initialization wizard. vagrant@TFB-all:~/FrameworkBenchmarks$ ./tfb --new This will walk you through the entire process of creating a new test to include in the suite. Resources Official Documentation Our official documentation can be found in the wiki. If you find any errors or areas for improvement within the docs, feel free to open an issue in this repo. Live Results Results of continuous benchmarking runs are available in real time here. Data Visualization If you have a results.json file that you would like to visualize, you can do that here. You can also attach a runid parameter to that url where runid is a run listed on tfb-status like so: https://www.techempower.com/benchmarks/#section=test&runid=fd07b64e-47ce-411e-8b9b-b13368e988c6. If you want to visualize them or compare different results files on bash, here is an unofficial plaintext results parser Contributing The community has consistently helped in making these tests better, and we welcome any and all changes. Reviewing our contribution practices and guidelines will help to keep us all on the same page. The contribution guide can be found in the TFB documentation. Join in the conversation in the Discussions tab, on Twitter, or chat with us on Freenode at #techempower-fwbm.
Read the full README on GitHub

What Hacker News says

10 sources
abetlen·Jun 5, 2019
Not OP but to answer #2, based on the benchmark code here [1] the difference is that actix-pg accesses the database through message passing in the actor system [2] while actix-core accesses it directly [3]. [1]. https://github.com/TechEmpower/FrameworkBenchmarks/tree/mast... [2]. https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast... [3]. https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
In Actix-web 1.0 – A small, pragmatic, and fast web framework for Rust
jchw·Jan 26, 2019Recommendation phrase
Something notable is that jlhttp and fasthttp are both using worker pools. fasthttp uses worker pools of goroutines, and jlhttp uses traditional thread pooling. Thread pooling is an effective solution to improve webserver performance, and it generally works well. In these synthetic benchmarks, you can't even really see much of a downside. In reality a lot of these benchmarks are only so good because they have requests that complete very quickly, and I think if you add a random sleep() into them many of them will just die outright because they can't handle that much concurrency and block waiting for free workers. You might think that is unrealistic, but consider that many people have Go servers that are making RPCs all over the place, and an actual large amount of time can just be spent waiting on other RPCs. It's a real thing! And if the
Read the rest
world were just responding to HTTP requests, obviously something like Goroutines would be overkill. But, one of my favorite uses of Goroutines was implementing a messaging server where each consumer, queue, exchange were all their own Goroutines. I was inspired by RabbitMQ for the design but unfortunately could not use it in this use case. Luckily Goroutines worked really great here and I was able to scale this thing up hugely. To me this is where they're really great: they're super flexible. They work pretty well for short-lived HTTP requests, but also great for entirely different and more complicated use cases. Looking back at the benchmark, one of the more interesting approaches here is go-prefork[1], which works by spawning n/2 executables with 2 threads each. I can only imagine the optimal amount of threads was complicated to determine and maybe even has something to do with hyperthreading. Of course the advantage here is the reduced amount of shared state that leads to less contention, and it does indeed show up on the benchmark. In this setup, it looks weird because there's no load balancer (could be something as simple as some iptables rules) or anything in front. In practice, this would be much akin to running separate instances on the same box, which is also a reasonable approach, and I used this approach myself when scheduling servers. Oddly, I don't think they tried the same approach for fasthttp. I think what else the benchmark shows is how clever you don't have to be in Go to get good performance. go-postgres is routinely in the middle of the pack and it is literally just using the standard library and goroutines in the most basic fashion. It's effectively not optimized. And in reality, in many cases with more complex servers, the overhead is low enough that it isn't worth your time to optimize it much more. [1]: https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
In Websocketd
rehemiau·Jan 6, 2019
There are more reasons, but - better configuration (tweaked to this benchmark / hardware). Bigger communities will try harder to tweak their benchmark config. The Phoenix one is probably just the default one or slightly tweaked. Is the SQL connection pool size ideal? Are all default Phoenix-added Plugs ("middlewares") needed here? Is the BEAM virtual machine config / flags ideal? Would using OTP releases be beneficial? - Elixir ecosystem is constantly improving the performance. The VM, language and packages versions should be updated. Elixir 1.6.5, Phoenix 1.3.2, and Ecto 2.1 are not recent. - Abstractions used (and amount of them, so amount of work done at run-time). Compare the Fortunes "handler" implementation in vertx-postgres [1] to the Phoenix one [2]. Raw SQL vs generated query, almost bare DB connection pool vs Repository abstract
Read the rest
ion, and it's just the "handler". But you wouldn't want to maintain a lot of low level code. - Typical functional language overhead. Copying (copying the conn when modifying it, Enum.sort on a list etc) is more expensive than modifying in-place. Again, functional code will be easier to maintain. But overall I think in the particular benchmark you linked, Phoenix isn't that bad. Latency is pretty low and consistent (0.5 ms min and 9.9 ms max (!)) thanks to the BEAM pre-emptive scheduler. And BEAM will scale well vertically. 1. https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast... 2. https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
In Would you still pick Elixir in 2019?

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