The top 10 implementations were implemented in C++, Ur and Java. Again, both undertow and undertow edge seem to be included three times in round 9 data table, which looks a bit strange for the best results table. CppCMS is the web development framework written in C++, that is aimed on development of high performance web application. It uses different web APIs, most noticably FastCGI, as a web layer and various databases as a storage backed.

  • While I’m not contesting this statement, but there wasn’t any mention about software versions, and since performance attributes tend to change over time between releases, this premise is not repeatable.
  • The top 10 in this category is occupied by test implementations based on C++, C, Java and Scala.
  • Development related discussions take place in an online forum and the source code repository is publicly available on GitHub.
  • My primary objectives were correctness, compositionality, and typesafety.

I’ve got a project on a 16G server – the data center doesn’t have anything bigger. Moving everything to a custom server or different data center to get to 24G or 32G is… Some time spent finding memory reductions is still worth it. As a related aside, we have an intention to eventually capture some additional statistics about the implementations such as source lines of code, total number of commits, and possibly lines of code of libraries . This model is not entirely without problems since the scalability rating is not relative to the throughput, so e.g. a poorly performing framework can end up having a great scalability rating. As a result, you’d have to look at these figures together.

Database updates test

C++ based test implementations dominate the top 4 spots with Lua, Ur and Java also in top 10. Only test implementations based on relational databases made it to top 10, leaving out MongoDB and Cassandra. Of course, every little improvement in performance required digging deeper for more ways to improve — and this is where the insanity begins. One annoying overhead for any web server is handling requests. When it comes to performance, strings are one of the worst data types to deal with in almost any language.

The bean validation specification was first released in 2009. This API uses annotations to set constraints on Java Beans. You then call the validation method on an annotated instance to find out if its valid. The reference, and most popular implementation is from Hibernate.

It seems to correspond to languages with a solid community behind them. But it is often easier to start by studying the language first. Each feature is quite important and mostly independant from each other. I tried to embrace most important topics concerning web frameworks with these four properties. I am fully concious some people might lack another important feature. Nonetheless the methodology used here can be easily replicated.

[Solved]-Is cpoll_cppsp framework type-safe as Ur/Web?-C++

(0.2 and above) SocketD web server multiplexer allows you to share the same port with multiple cppsp web application hosts, and even between cppsp and another web server (lighttpd, nginx, …). SocketD supports hostname and request URI matching, but request URI matching does not work well with HTTP keep-alive. As a little bonus, since the Scala API only uses immutable data structure, it’s completely Thread safe. Hacking my original code for 5 minutes, I came up with a version using my multi-core processor to it’s fullest. It does not matter if Java kills Scala on micro-benchmarks. Because Java lacks essential constructs, it forces you to rely on workarounds like using reflection.

When you develop day to day, it’s rare you need to consider what operators the processor will use to accomplish the task — but when you’re fighting for every nano- and microsecond… https://topbitcoinnews.org/ well, here we are. There is a possible bug in glibc where if large chunks of memory are malloc()’d and free()’d, glibc repeatedly calls mprotect(), which is very expensive.

512Mbps using 22% CPU, very respectable and plenty of CPU available. I’m guessing bandwidth capped and split between the VMs on the base hardware; its a fairly small and affordable VM. Bearing in mind max TCP throughput, per connection, is bounded by latency, so two VMs connecting across a datacenter will perform worse than two machines next to each other directly connected via a switch.

This is the most complex test that aims to exercise the full framework stack from request routing through business logic execution, database access, templating and response generation. Top 10 frameworks in this test are based on Dart, Java, Clojure, PHP and C# languages and they use MongoDB and MySQL databases. Performance and scalability are often high priority concerns.

Some interesting observations could be made just by looking at the raw data. In addition to comparing throughput, it’s also interesting to compare how well frameworks scale. How Much Does A Taxi App Development Cost in 2022 One way of quantifying scalability is to take test implementation throughput figures for the lowest and highest concurrency level per framework and plot them on a 2-D plane.

cpoll_cppsp

I think the idea of a “meaningless benchmark” has become a dogma. Can you possibly know all the complexities that an app will contain when benchmarking a framework? No, but that doesn’t make baseline benchmarks useless. A short description of the hardware and some other test environment parameters is available on the benchmark project web site. However, the environment setup (hardware + software) is expected to change over time, so this information should be documented per round. Also, Linux distribution minor release or the exact Linux kernel version don’t appear to be identified.

The only difference between the two seems to be Jackson JSON library version numbers. One of the very common problem in programming is data validation. In a word, we want to make sure that every incoming data has the correct structure. We need to discriminate unsafe external inputs from safe, compiler validated data.

Web Framework Benchmarks – Round 10

I need to know which one is the best in terms of execution speed+resource usage (as that should be the main reason for choosing C++ for web development), stability and security. As soon as you throw a php framework on top though, it sinks to the bottom of the benchmarks. Doesn’t look to be “an order of magnitude faster” – 200% faster in some cases – certainly nice numbers, but not a massive game changer for many (yet?). It is perfectly fine to not squeeze every drop from your hardware and pick Go or Lua. All the way down to x4, in other words not an order of magnitutde.

A company called TechEmpower has started a project called TechEmpower Framework Benchmarks, or TFB for short, that aims to compare the performance of different web frameworks. The project publishes benchmark results that application developers can use to make more informed decisions when selecting frameworks. What’s particularly interesting about FrameworkBenchmarks, is that it’s a collaborative effort conducted in an open manner. Development related discussions take place in an online forum and the source code repository is publicly available on GitHub. Doing test implementation development in the open is important for enabling peer review and it allows implementations to evolve and improve over time. The project implements performance tests for a wide variety of frameworks, and chances are that the ones that you’re planning to use are included.

Openly published test implementations are not only useful for producing benchmark data, but can also be used by framework developers to communicate framework performance related best practices to application developers. They also allow framework developers to receive reproducible performance benchmarking feedback and data for optimization purposes. In this case adding support for a new database involved creating a new DB schema, test data generation and automating database installation and configuration. Resin was chosen as the Java application server over Apache Tomcat and other servlet containers due to performance reasons.

cpoll_cppsp

To find that, we need to go back to Round 9 in 2014 — the last time ASP.NET was even listed. The fastest framework was “cpoll_cppsp”, which handled 6,738,911 requests per second. That translates to 3.2 million requests per second – which is outperforming all but the top 5 on the 10 GbE directly connected 40 HT core Peak tests.

JSON serialization

They had two primary reasons for this massive undertaking. First, getting started on your ASP.NET app was a multiple-hour endevour — as in, four hours after you decided you wanted to try ASP.NET, you were ready to write your first line of code. (We covered how much they’ve improved that experience in a previous blog post, Writing.NET Applications With Visual Studio Code.) Second, they wanted to improve ASP.NET’s performance as much as possible. CPPSP (C++ Server Pages) is an open source web application framework similar to ASP.NET. It features a template parser that parses, compiles, and loads CPPSP pages automatically at runtime. CPPSP pages have a very similar syntax to ASP and ASP.NET, where all code is considered HTML by default, and server-side active code can be embedded using “”.

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Top performing 10 frameworks were based on Java, C++, Lua and PHP languages and are using MySQL, PostgreSQL and MongoDB databases. Both use MySQL DB. Spring based test implementation performance was a bit of a disappointment. I was a bit disappointed with the performance of the servlet3-cass test implementation in the database tests. Unfortunately, there’s no resource usage or profiling data available for the test run, and as I don’t have access to a real performance test environment myself, so it’s difficult to analyse potential bottlenecks further. Where the previous test exercised a single database query per request this test does a variable number of database queries per request. Again, I would’ve assumed this test would measure the backend database performance more than the framework performance, but it seems that framework and database access method overhead can also contribute significantly.

Too bad memory is not measured/displayed as well. For many cloud-hosted servers, you will end up paying for memory, rather than CPU. In my last project I tried to use scalatra with slick, and while I really liked scalatra, slick made me go nuts. I had to jump over so many hoops that it was just a pain. When ever I feel like that, a few hours with either the Java or Scala persistance frameworks rapidly cures me of it.

TFB executes Java based performance implementations in the Resin web container, and after a while of puzzlement about the errors, I decided to test the code in other web containers, namely Tomcat and Jetty. It turned out that I had bumped into 1 Resin bug and 2 Tomcat bugs related to servlet asynchronous processing support. Fortunately, since then framework installation procedure has been compartmentalized, so it’s possible to install just the framework that you’re developing tests for. Also, recently the project has added support for fully automated development environment setup with Vagrant, which is a great help. Another excellent addition is Travis CI integration that allows test implementation developers to gain additional assurance that their code is working as expected also outside their sandbox.