

Find out what your peers are saying about Apache, OpenText, Tricentis and others in Performance Testing Tools.
With Apache JMeter, I have gained great statistics for performance and server metrics.
I have not seen a return on investment right now, as there is no improvement in Apache JMeter and reduction in cost, but I save time and reduce costs with Apache JMeter.
With the introduction of Appium MCP, productivity has increased to 10x, meaning very few QA personnel are now needed to write automation.
With AI models ChatGPT, troubleshooting issues has become very easy for us.
The support for Apache JMeter is excellent.
Apache JMeter has strong support through its vast Java-based community on platforms like Stack Overflow.
Since Appium is open-source, I do not observe any formal customer support.
We do have some methods where we can distribute the complete load between multiple systems and then try to do our testing.
JMeter is highly scalable, easily handling increased loads through the use of multiple servers.
This restricts the number of users and necessitates increasing load agents or distributing the script across multiple machines.
Appium's scalability for my projects has significantly increased our speed of execution and delivery, achieving up to 10x faster results.
JMeter performs exceptionally well, especially in non-GUI mode, which supports high loads efficiently.
Several necessary features still need improvements, specifically in terms of reports and additional functionalities compared to other commercial tools.
Previous versions of Apache JMeter were a little unstable, but the new versions are very stable.
Appium is much more stable now compared to the 1.0 version.
With AI becoming more prominent, they can implement features where it can generate code by itself based on the results or provide suggestions.
Currently, we need to use multiple separate JMeter instances to simulate reductions in load, which isn't ideal.
The tool needs improvements related to client-side metrics, integrating with tools like YSlow or HTTP Watch, and enhancing mobile testing capabilities.
A community needs to emerge, driven by a set of industry leaders who can help people and contribute to the community, especially since platforms like Stack Overflow have diminished in relevance due to the rise of AI.
Using JMeter helps us avoid additional costs for high-load testing since it is open-source and allows for unlimited virtual users at no extra cost.
My experience with pricing, setup cost, and licensing is that the cost and license are free because Apache JMeter is open source.
It's a cost-effective solution.
My experience with pricing, setup cost, and licensing for Appium is straightforward since it is open-source, and I currently have no concerns about using it.
JMeter facilitates scripting capabilities, which include options for Groovy scripts.
It's useful for both the person conducting the test and the higher management, like project managers or senior executives, who may not know about the test.
Despite being open source, it offers features comparable to paid tools.
In Appium version 3.0, many things have been made decoupled, which is really helpful with different drivers and plugins for different platforms, providing a lot of freedom to an SDET or any QA members automating mobile applications.
| Product | Mindshare (%) |
|---|---|
| Apache JMeter | 9.1% |
| OpenText Professional Performance Engineering (LoadRunner Professional) | 16.6% |
| Tricentis NeoLoad | 13.9% |
| Other | 60.4% |
| Product | Mindshare (%) |
|---|---|
| Appium | 2.8% |
| OutSystems | 9.2% |
| Mendix | 8.6% |
| Other | 79.4% |


| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 23 |
| Large Enterprise | 62 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 6 |
| Large Enterprise | 20 |
Apache JMeter is a versatile, open-source tool designed for performance and load testing, widely recognized for its user-friendly interface and robust test automation capabilities. It supports a range of protocols and integrates seamlessly into various environments, making it ideal for high-load scenarios.
Apache JMeter stands out in performance testing for its ability to handle high transactions per second and perform distributed load testing effectively. Its open-source nature and cost-effectiveness are enhanced by its user-friendly GUI, which simplifies the testing process. Despite memory consumption concerns, Apache JMeter remains a top choice due to its large community support, comprehensive scripting capabilities, and easy integration with CI/CD pipelines, allowing for continuous automated testing. Its robust protocol support meets diverse testing needs.
What are Apache JMeter's key features?In industries like finance and banking, Apache JMeter is used extensively for performance validation to ensure system robustness under heavy user loads. It's integrated into CI/CD pipelines for automated testing processes, allowing organizations to simulate real-world scenarios and ensure high-performance standards.
Appium facilitates seamless automation of iOS and Android mobile applications, interfacing smoothly with CI/CD pipelines and enabling cross-platform development. Its open-source framework supports diverse coding languages, enhancing test automation.
Appium stands out for its ability to automate mobile apps across multiple platforms, backed by a strong community and extensive language compatibility. It integrates with continuous integration and delivery workflows, with robust tools like Appium Inspector enhancing element identification. It offers an interface familiar to Selenium users and supports versatile scripting, easing the mobile app testing process for developers. While it provides scalability and simple connectivity, users seek enhancements in stability, speed, and platform integration, specifically with iOS and cloud solutions.
What are Appium's Key Features?Appium is widely utilized in industries such as healthcare, logistics, and construction for the automation of iOS and Android apps. Companies integrate it into their DevOps practices for continuous testing, using it in hybrid deployments and linking with tools like GitHub Actions and Jira for efficient test management.
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