1. Both Are Open Source
One of the most crucial questions to ask is what a tool’s licensing scope is. If a tool is open source, you can achieve nearly any performance test objective you choose without paying anything extra. JMeter and Locust, both open source, are no exception.
Locust was built by a small group of community-driven developers and is released under the MIT license, whereas JMeter was produced by Apache and is licensed under the Apache 2.0 license. Both of these tools are open source, which means you are free to use them.
2. Load Test Creation And Maintenance
A performance test pipeline has three basic steps: create, execute, and analyze. It’s no secret that the initial step generally takes the most time. There may be exceptions to this rule, but if your application is well-written, you should not spend more time on test execution and analysis than on test development. As a result, this stage is critical to our comparison. Because being familiar with a performance tool necessitates first and foremost being comfortable with the process of creating tests.
The GUI mode of JMeter is the most common way to write a load test. The JMeter GUI mode is a desktop client that lets you build tests quickly and simply without writing a single line of code (until you need to create a tricky test). As an example, consider the following scenario:
JMeter is extremely easy to use, and even a novice engineer can read and write basic scenarios with ease. You can, however, use Java to run code in both GUI and non-GUI mode if necessary. However, this way is not popular across the JMeter community due to the complexity of scripts implementation (as JMeter was designed to be used with GUI mode) and lack of documentation on how to make such scripts.
On the other side, Locust is all about code. You’ll need at least some basic Python coding skills to feel comfortable developing performance tests. This is the same test scenario as before, only this time Locust is used:
Scripts created in Locust appear to be quite clear, but when you’re working on a large, complex test, it might be difficult to review.
Having all of your tests in code, on the other hand, is a huge benefit since it allows you to immediately correct them without having to use the UI. If you’re running your script on the server and don’t have access to a desktop client, this may be really useful. Using a version control system like Git, coding also allows you to validate any test changes made by your peers.