As many others have alluded, the comparison lacks context.
At the time of its release, the async approach of node.js was revolutionary. Since then other languages and web frameworks have been adopting the approaches they took mainstream.

To understand what the difference meant, you need to simulate a blocking request that represents some IO workload, such as a database request. In a thread-per-request system, this will exhaust the threadpool and new requests will be put in to a queue waiting for an available thread.
With non-blocking-io frameworks this does not happen.

Consider this node.js server that waits 1 second before responding

const server = http.createServer((req, res) => {
  setTimeout(() => {
    res.statusCode = 200;
    res.end();
  }, 1000);
});

Now let's throw 100 concurrent conenctions at it, for 10s. So we expect about 1000 requests to complete.

$ wrk -t100 -c100 -d10s http://localhost:8000
Running 10s test @ http://localhost:8000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.01s    10.14ms   1.16s    99.57%
    Req/Sec     0.13      0.34     1.00     86.77%
  922 requests in 10.09s, 89.14KB read
Requests/sec:     91.34
Transfer/sec:      8.83KB

As you can see we get in the ballpark with 922 completed.

Now consider the following asp.net code, written as though async/await were not supported yet, therefore dating us back to the node.js launch era.

app.Run((context) =>
{
    Thread.Sleep(1000);
    context.Response.StatusCode = 200;
    return Task.CompletedTask;
});

$ wrk -t100 -c100 -d10s http://localhost:5000
Running 10s test @ http://localhost:5000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.08s    74.62ms   1.15s   100.00%
    Req/Sec     0.00      0.00     0.00    100.00%
  62 requests in 10.07s, 5.57KB read
  Socket errors: connect 0, read 0, write 0, timeout 54
Requests/sec:      6.16
Transfer/sec:     566.51B

62! Here we see the limit of the threadpool. By tuning it up we could get more concurrent requests happening, but at the cost of more server resources.

For these IO-bound workloads, the move to avoid blocking the processing threads was that dramatic.

Now let's bring it to today, where that influence has rippled through the industry and allow dotnet to take advantage of its improvements.

app.Run(async (context) =>
{
    await Task.Delay(1000);
    context.Response.StatusCode = 200;
});

$ wrk -t100 -c100 -d10s http://localhost:5000
Running 10s test @ http://localhost:5000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.01s    19.84ms   1.16s    98.26%
    Req/Sec     0.12      0.32     1.00     88.06%
  921 requests in 10.09s, 82.75KB read
Requests/sec:     91.28
Transfer/sec:      8.20KB

No surprises here, we now match node.js.

So what does all this mean?

Your impressions that node.js is the "fastest" come from an era we are no longer living in. Add to that it was never node/js/v8 that were "fast", it was that they broke the thread-per-request model. Everyone else has been catching up.

If your goal is the fastest possible processing of single requests, then look at the serious benchmarks instead of rolling your own. But if instead what you want is simply something that scales to modern standards, then go for whichever language you like and make sure you are not blocking those threads.

Disclaimer: All code written, and tests run, on an ageing MacBook Air during a sleepy Sunday morning. Feel free to grab the code and try it on Windows or tweak to your needs - https://github.com/csainty/nodejs-vs-aspnetcore

Answer from Chris Sainty on Stack Overflow
Top answer
1 of 2
210

As many others have alluded, the comparison lacks context.
At the time of its release, the async approach of node.js was revolutionary. Since then other languages and web frameworks have been adopting the approaches they took mainstream.

To understand what the difference meant, you need to simulate a blocking request that represents some IO workload, such as a database request. In a thread-per-request system, this will exhaust the threadpool and new requests will be put in to a queue waiting for an available thread.
With non-blocking-io frameworks this does not happen.

Consider this node.js server that waits 1 second before responding

const server = http.createServer((req, res) => {
  setTimeout(() => {
    res.statusCode = 200;
    res.end();
  }, 1000);
});

Now let's throw 100 concurrent conenctions at it, for 10s. So we expect about 1000 requests to complete.

$ wrk -t100 -c100 -d10s http://localhost:8000
Running 10s test @ http://localhost:8000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.01s    10.14ms   1.16s    99.57%
    Req/Sec     0.13      0.34     1.00     86.77%
  922 requests in 10.09s, 89.14KB read
Requests/sec:     91.34
Transfer/sec:      8.83KB

As you can see we get in the ballpark with 922 completed.

Now consider the following asp.net code, written as though async/await were not supported yet, therefore dating us back to the node.js launch era.

app.Run((context) =>
{
    Thread.Sleep(1000);
    context.Response.StatusCode = 200;
    return Task.CompletedTask;
});

$ wrk -t100 -c100 -d10s http://localhost:5000
Running 10s test @ http://localhost:5000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.08s    74.62ms   1.15s   100.00%
    Req/Sec     0.00      0.00     0.00    100.00%
  62 requests in 10.07s, 5.57KB read
  Socket errors: connect 0, read 0, write 0, timeout 54
Requests/sec:      6.16
Transfer/sec:     566.51B

62! Here we see the limit of the threadpool. By tuning it up we could get more concurrent requests happening, but at the cost of more server resources.

For these IO-bound workloads, the move to avoid blocking the processing threads was that dramatic.

Now let's bring it to today, where that influence has rippled through the industry and allow dotnet to take advantage of its improvements.

app.Run(async (context) =>
{
    await Task.Delay(1000);
    context.Response.StatusCode = 200;
});

$ wrk -t100 -c100 -d10s http://localhost:5000
Running 10s test @ http://localhost:5000
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     1.01s    19.84ms   1.16s    98.26%
    Req/Sec     0.12      0.32     1.00     88.06%
  921 requests in 10.09s, 82.75KB read
Requests/sec:     91.28
Transfer/sec:      8.20KB

No surprises here, we now match node.js.

So what does all this mean?

Your impressions that node.js is the "fastest" come from an era we are no longer living in. Add to that it was never node/js/v8 that were "fast", it was that they broke the thread-per-request model. Everyone else has been catching up.

If your goal is the fastest possible processing of single requests, then look at the serious benchmarks instead of rolling your own. But if instead what you want is simply something that scales to modern standards, then go for whichever language you like and make sure you are not blocking those threads.

Disclaimer: All code written, and tests run, on an ageing MacBook Air during a sleepy Sunday morning. Feel free to grab the code and try it on Windows or tweak to your needs - https://github.com/csainty/nodejs-vs-aspnetcore

2 of 2
13

Node Frameworks like Express and Koa have a terrible overhead. "Raw" Node is significantly faster.

I haven't tried it, but there's a newer framework that gets very close to "Raw" Node performance: https://github.com/aerojs/aero

(see benchmark on that page)

update: Here are some figures: https://github.com/blitzprog/webserver-benchmarks

Node:
    31336.78
    31940.29
Aero:
    29922.20
    27738.14
Restify:
    19403.99
    19744.61
Express:
    19020.79
    18937.67
Koa:
    16182.02
    16631.97
Koala:
    5806.04
    6111.47
Hapi:
    497.56
    500.00

As you can see, the overheads in the most popular node.js frameworks are VERY significant!

Top answer
1 of 5
414

Being FAST and handling lots of LOAD are two different things. A server that's really FAST at serving one request per second might totally croak if you send it 500 requests per second (under LOAD).

You also have to consider static (and cached) vs dynamic pages. If you're worried about static pages, then IIS is probably going to beat node because IIS uses kernel-mode caching, which means that requests which request a static page are not even going to get out of the kernel.

I'm guessing that you're looking for a comparison between ASP.NET and node. In this battle, after everything's been compiled/interpreted you're probably going to be pretty close in performance. Maybe .NET's a little FASTER or maybe node's a little FASTER, but it's probably close enough that you don't care. I'd bet on .NET, but I don't know for sure.

The place that node is really compelling is for handling LOAD. This is where the technologies really differ. ASP.NET dedicates a thread for each request from its thread pool, and once ASP.NET has exhausted all the available threads requests begin to get queued up. If you're serving "Hello World" apps like the example by @shankar, then this might not matter that much because the threads aren't going to be blocked and you're going to be able to handle a lot of requests before you run out of threads. The problem with the ASP.NET model comes when you start making I/O requests that block the thread (call to a DB, make an http request to a service, read a file from disk). These blocking requests mean that your valuable thread from the thread pool is doing nothing. The more blocking you have, the less LOAD your ASP.NET app is going to be able to serve.

To prevent this blocking, you use I/O completion ports which don't require holding a thread while you wait for a response. ASP.NET supports this, but unfortunately many of the common frameworks/libraries in .NET DON'T. For example, ADO.NET supports I/O completion ports, but Entity Framework doesn't use them. So you can build an ASP.NET app that's purely asynchronous and handles lots of load, but most people don't because it isn't as easy as building one that's synchronous, and you might not be able to use some of your favorite parts of the framework (like linq to entities) if you do.

The problem is that ASP.NET (and the .NET Framework) were created to be un-opinionated about asynchronous I/O. .NET doesn't care if you write synchronous or asynchronous code, so it's up to the developer to make this decision. Part of this is because threading and programming with asynchronous operations was thought to be "hard", and .NET wanted to make everyone happy (noobs and experts). It got even harder because .NET ended up with 3-4 different patterns for doing async. .NET 4.5 is trying to go back and retrofit the .NET framework to have an opinionated model around async IO, but it may be a while until the frameworks you care about actually support it.

The designers of node on the other hand, made an opinionated choice that ALL I/O should be async. Because of this decision, node designers were also able to make the decision that each instance of node would be single threaded to minimize thread switching, and that one thread would just execute code that had been queued. That might be a new request, it might be the callback from a DB request, it might be the callback from a http rest request you made. Node tries to maximize CPU efficiency by eliminating thread context switches. Because node made this opinionated choice that ALL I/O is asynchronous, that also means that all it's frameworks/add-ons support this choice. It's easier to write apps that are 100% async in node (because node forces you to write apps that are async).

Again, I don't have any hard numbers to prove one way or another, but I think node would win the LOAD competition for the typical web app. A highly optimized (100% async) .NET app might give the equivalent node.js app a run for it's money, but if you took an average of all the .NET and all the node apps out there, on average node probably handles more LOAD.

2 of 5
53

I did a rudimentary performance test between nodejs and IIS. IIS is about 2.5 times faster than nodejs when dishing out "hello, world!". code below.

my hardware: Dell Latitude E6510, Core i5 (dual core), 8 GB RAM, Windows 7 Enterprise 64 bit OS

node server

runs at http://localhost:9090/
/// <reference path="node-vsdoc.js" />
var http = require("http");
http.createServer(function (request, response) {
response.writeHead(200, { "Content-Type": "text/html" });
response.write("<p>hello, world!</p>");
response.end();
}).listen(9090);

default.htm

hosted by iis at http://localhost/test/
<p>hello, world!</p>

my own benchmark program using task parallel library:

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Net;
using System.Threading;
using System.Threading.Tasks;
using System.Diagnostics;

namespace HttpBench
{
class Program
{
    private int TotalCount = 100000;
    private int ConcurrentThreads = 1000;
    private int failedCount;
    private int totalBytes;
    private int totalTime;
    private int completedCount;
    private static object lockObj = new object();

    /// <summary>
    /// main entry point
    /// </summary>
    static void Main(string[] args)
    {
        Program p = new Program();
        p.Run(args);
    }

    /// <summary>
    /// actual execution
    /// </summary>
    private void Run(string[] args)
    {
        // check command line
        if (args.Length == 0)
        {
            this.PrintUsage();
            return;
        }
        if (args[0] == "/?" || args[0] == "/h")
        {
            this.PrintUsage();
            return;
        }

        // use parallel library, download data
        ParallelOptions options = new ParallelOptions();
        options.MaxDegreeOfParallelism = this.ConcurrentThreads;
        int start = Environment.TickCount;
        Parallel.For(0, this.TotalCount, options, i =>
            {
                this.DownloadUrl(i, args[0]);
            }
        );
        int end = Environment.TickCount;

        // print results
        this.Print("Total requests sent: {0}", true, this.TotalCount);
        this.Print("Concurrent threads: {0}", true, this.ConcurrentThreads);
        this.Print("Total completed requests: {0}", true, this.completedCount);
        this.Print("Failed requests: {0}", true, this.failedCount);
        this.Print("Sum total of thread times (seconds): {0}", true, this.totalTime / 1000);
        this.Print("Total time taken by this program (seconds): {0}", true, (end - start) / 1000);
        this.Print("Total bytes: {0}", true, this.totalBytes);
    }

    /// <summary>
    /// download data from the given url
    /// </summary>
    private void DownloadUrl(int index, string url)
    {
        using (WebClient client = new WebClient())
        {
            try
            {
                int start = Environment.TickCount;
                byte[] data = client.DownloadData(url);
                int end = Environment.TickCount;
                lock (lockObj)
                {
                    this.totalTime = this.totalTime + (end - start);
                    if (data != null)
                    {
                        this.totalBytes = this.totalBytes + data.Length;
                    }
                }
            }
            catch
            {
                lock (lockObj) { this.failedCount++; }
            }
            lock (lockObj)
            {
                this.completedCount++;
                if (this.completedCount % 10000 == 0)
                {
                    this.Print("Completed {0} requests.", true, this.completedCount);
                }
            }
        }
    }

    /// <summary>
    /// print usage of this program
    /// </summary>
    private void PrintUsage()
    {
        this.Print("usage: httpbench [options] <url>");
    }

    /// <summary>
    /// print exception message to console
    /// </summary>
    private void PrintError(string msg, Exception ex = null, params object[] args)
    {
        StringBuilder sb = new System.Text.StringBuilder();
        sb.Append("Error: ");
        sb.AppendFormat(msg, args);
        if (ex != null)
        {
            sb.Append("Exception: ");
            sb.Append(ex.Message);
        }
        this.Print(sb.ToString());
    }

    /// <summary>
    /// print to console
    /// </summary>
    private void Print(string msg, bool isLine = true, params object[] args)
    {
        if (isLine)
        {
            Console.WriteLine(msg, args);
        }
        else
        {
            Console.Write(msg, args);
        }
    }

}
}

and results:

IIS: httpbench.exe http://localhost/test

Completed 10000 requests.
Completed 20000 requests.
Completed 30000 requests.
Completed 40000 requests.
Completed 50000 requests.
Completed 60000 requests.
Completed 70000 requests.
Completed 80000 requests.
Completed 90000 requests.
Completed 100000 requests.
Total requests sent: 100000
Concurrent threads: 1000
Total completed requests: 100000
Failed requests: 0
Sum total of thread times (seconds): 97
Total time taken by this program (seconds): 16
Total bytes: 2000000

nodejs: httpbench.exe http://localhost:9090/

Completed 10000 requests.
Completed 20000 requests.
Completed 30000 requests.
Completed 40000 requests.
Completed 50000 requests.
Completed 60000 requests.
Completed 70000 requests.
Completed 80000 requests.
Completed 90000 requests.
Completed 100000 requests.
Total requests sent: 100000
Concurrent threads: 1000
Total completed requests: 100000
Failed requests: 0
Sum total of thread times (seconds): 234
Total time taken by this program (seconds): 27
Total bytes: 2000000

conclusion: IIS is faster than nodejs by about 2.5 times (on Windows). This is a very rudimentary test, and by no means conclusive. But I believe this is a good starting point. Nodejs is probably faster on other web servers, on other platforms, but on Windows IIS is the winner. Developers looking to convert their ASP.NET MVC to nodejs should pause and think twice before proceeding.

Updated (5/17/2012) Tomcat (on windows) seems to beat IIS hands down, about 3 times faster than IIS in dishing out static html.

tomcat

index.html at http://localhost:8080/test/
<p>hello, world!</p>

tomcat results

httpbench.exe http://localhost:8080/test/
Completed 10000 requests.
Completed 20000 requests.
Completed 30000 requests.
Completed 40000 requests.
Completed 50000 requests.
Completed 60000 requests.
Completed 70000 requests.
Completed 80000 requests.
Completed 90000 requests.
Completed 100000 requests.
Total requests sent: 100000
Concurrent threads: 1000
Total completed requests: 100000
Failed requests: 0
Sum total of thread times (seconds): 31
Total time taken by this program (seconds): 5
Total bytes: 2000000

updated conclusion: i ran the benchmark program multiple times. Tomcat appears to be the fastest server in dishing out STATIC HTML, ON WINDOWS.

Updated (5/18/2012) Previously I had 100,000 total requests with 10,000 concurrent requests. I increased it to 1,000,000 total requess and 100,000 concurrent requests. IIS comes out as the screaming winner, with Nodejs fairing the worst. I have tabularized the results below:

.

Discussions

Performance of node compared to dotnet
In general OP c# can be faster than node because it is compiled and then jitted where as JavaScript is parsed from source and then jitted by v8. C# has more options for tasks, for example true parallel programming that can efficiently take advantage of all CPU cores and non blocking concurrency. C# generally can handle memory intensive operations better with types and structs. Node however uses C++ under the hood for tasks that JavaScript can’t effectively do like networking, the file system or multi threading. While node makes use of C++ v8 still interprets JavaScript and executes it on a single thread. More on reddit.com
🌐 r/node
35
12
March 24, 2025
Ask HN: Node vs. .NET Core (2024 edition)
https://news.ycombinator.com/item?id=13034904 · How are things looking now after 8 years More on news.ycombinator.com
🌐 news.ycombinator.com
51
13
April 19, 2024
What's the truth? - Reg. Node vs dotnet core
LOL, is this post from 2009? Here are a couple of links for ya: .NET Core or Node.js? [We increased throughput by 2,000%] TechEmpower rating TechEmpower Fortunes On the TechEmpower pages, notice the places for aspcore and nodejs. Yes, the tests are 2022, but it is unlikely that Node has jumped 200 places in a year to reach asp.net core. TLDR: .NET Core is the fastest mainstream fully featured application framework right now, and even more performance improvements are coming with .NET 8. Edit: and Node isn’t even a framework, it’s a barebones JavaScript runtime. More on reddit.com
🌐 r/dotnet
55
32
September 25, 2023
is Node a better choice for backend than ASP .NET?
Asking in a node js subreddit More on reddit.com
🌐 r/node
66
28
March 30, 2022
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September 25, 2023 -

I see lot of blogs saying that node.js performs better because of non-blocking I/O model. But .NET core also has async model now.In-fact in my project I use dotnet core with complete async methods. I assume async-await is nothing but a non-blocking I/O model.

I couldn't find any benchmarks that says one is faster than other. Does anyone here has compared it? This & This benchmark says dotnet is much much efficient than nodejs in 2022.

What is the truth in yr.2023?

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.NET Core vs Node.js: What Should You Choose? | by inVerita | The Startup | Medium
January 31, 2022 - The first battle is going to be between .NET Core and Node.js. These are two renowned, publicly available development environments that scale, fasten, speed up, and empower the development process. Both .NET Core and Node.js have pros and cons, and each is better with every release.
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medium.com › @sohail.aslam9987 › a-comprehensive-comparative-analysis-of-net-core-vs-node-js-for-web-development-a-term-report-c1e69f0281ed
A Comprehensive Comparative Analysis of .NET Core vs. Node.js for Web Development — A Term Report | by Muhammad Sohail Aslam | Medium
June 11, 2025 - Whereas. NET Core provides a highly reliable and type-safe foundation built on C# optimized for enterprise applications, and Node.js provides a lightweight event-driven JavaScript runtime designed to perform I/O-bound operations.