Performance Tip: for vs. foreach in Microsoft .NET

Collections are one of the most commonly used types in programming. For any program that uses data, you will be dealing with collections. One of the most common things we do is to iterate over the collection to process the data. There are three main ways to iterate over a collection in .NET.


For is a common statement in many programming languages by using a counter variable to iterate over a collection.

for (int personCount = 0; personCount < _personCollection.Count - 1; 
    var name = _personCollection[personCount].FirstName;


Foreach was the statement I usually used because it’s cleaner and easier to read.

foreach (var person in _personCollection)
    var name = person.FirstName;

foreach with AsParallel()

AsParallel() is part of LINQ and could increase performance if there is a sugnificant load with processing the data.

foreach (var person in _personCollection.AsParallel())
    var name = person.FirstName;


I’ve done a lot of benchmarking using for, foreach and foreach AsParallel() for my book on code performance. I ran the benchmark four times using a collection count of 100, 500, 2000 and 5000. Included in this test is the comparison between .NET Clr 4.7.2 and .NET Core 2.2. Below are the results.

Test Runtime Collection Count Mean (ns) CLR vs CORE Difference
for Clr 4.7.2 100 108.8216
foreach Clr 4.7.2 100 308.1016
foreach AsParallel() Clr 4.7.2 100 853.7294
for Core 2.2 100 108.3985 -0.4231
foreach Core 2.2 100 334.339 26.2374
foreach AsParallel() Core 2.2 100 821.127 -32.60
for Clr 4.7.2 500 672.2033
foreach Clr 4.7.2 500 1,619.09
foreach AsParallel() Clr 4.7.2 500 3,881.51
for Core 2.2 500 671.033 -1.17
foreach Core 2.2 500 1,662.23 43.14
foreach AsParallel() Core 2.2 500 3,626.62 -254.89
for Clr 4.7.2 2000 3,400.98
foreach Clr 4.7.2 2000 7,615.78
foreach AsParallel() Clr 4.7.2 2000 18,726.19
for Core 2.2 2000 3,422.70 21.72
foreach Core 2.2 2000 7,444.41 -171.36
foreach AsParallel() Core 2.2 2000 13,814.03 -4,912.16
for Clr 4.7.2 5000 10,242.85
foreach Clr 4.7.2 5000 21,524.22
foreach AsParallel() Clr 4.7.2 5000 38,018.76
for Core 2.2 5000 10,330.39 87.54
foreach Core 2.2 5000 21,290.93 -233.29
foreach AsParallel() Core 2.2 5000 35,289.98 -2,728.78

The test was done using a business object called Person to mimic the a real world object. As you can see, using for is around 2-3 times faster than foreach! Wow, I was surprised when I first saw this. The benchmark comparing the .NET Clr 4.7.2 to .NET Core 3 produced similar results.

In most tests, .NET Core is faster than the Clr. Moving to .NET Core should be on your team’s roadmap if you aren’t already moving to it.


My recommendation is to always use for and avoid foreach. I would also avoid using foreach with AsParallel(), unless there is load during the processing of the data. In all my open-source projects and any code that I work on in my contracts, I am always using for from now on.

Of course, you should always benchmark your code to see how for, foreach, do and while looping performs in your own projects and servers.

To learn more about this subject and a lot more, pick up a copy of my book Rock Your Code: Code & App Performance for Microsoft .NET. Do you have any performance tips when using collections? Please make a comment below.

4 thoughts on “Performance Tip: for vs. foreach in Microsoft .NET

  1. Hi Dave, using foreach with AsParallel() is not how it is supposed to be used. Instead you should use AsParallel().ForAll.
    I got the following results on 1k items with 100ms delay on each iteration:
    Execution with [for] took 109500ms
    Execution with [foreach AsParallel] took 109378ms
    Execution with [AsParallel().ForAll] took 13734ms

    Here is my source for this test:

    Console.WriteLine(“AsParallel Test”);

    var arr = new int[1000];

    Stopwatch stp = new Stopwatch();
    for (int i = 0; i {
    Console.WriteLine($”Execution with [AsParallel().ForAll] took {stp.ElapsedMilliseconds}ms”);

    Console.WriteLine(“Press any key to exit”);

  2. “I would also avoid using foreach with AsParallel(),”
    The code sample that is being run here is very basic and I suspect the overhead of creating new threads isn’t worth the cost for this. I expect it would be better if the internal workload inside each loop iteration was heavier. You would then get much more benefit from multi threading as each process would be spending more time doing the work rather than starting and stopping threads.

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