Top 5 JMeter Alternatives

By Boris Seleznev, updated December 20, 2024.

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Boris Seleznev

Boris Seleznev is a seasoned performance engineer with over 10 years of experience in the field. Throughout his career, he has successfully delivered more than 200 load testing projects, both as an engineer and in managerial roles. Currently, Boris serves as the Professional Services Director at PFLB, where he leads a team of 150 skilled performance engineers.

Reviewed by Yuri Kovalov.

Reviewed by

Yuri Kovalov

Yuri Kovalov, an MBA and Stanford University-certified technical entrepreneur, has over 20 years of experience in the performance testing field. In 2008, Yuri founded Performance Lab, a leading performance testing company with over 150 performance engineers. The company completes more than 50 performance testing projects annually for enterprise customers. In 2022, Yuri launched PFLB, a Silicon Valley-based SaaS company offering an AI-powered load testing platform.

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It’s hard to find someone in the performance testing community who hasn’t heard of Apache JMeter. We love it for being open-source, free, feature-rich, protocol-friendly, and easily extendable. While JMeter remains a favorite, there are other tools that offer unique strengths and advantages.

This article presents a comprehensive list of the top 5 JMeter alternatives, highlighting their key features and comparisons. Whether you’re looking for advanced analytics, better scalability, or specialized protocol support, these tools provide excellent options to improve your performance testing toolkit.

Explore these alternatives to find the one that best fits your testing needs.

What Are Apache JMeter’s Weaknesses?

In 2023, the year when the tool itself turned 25 years old – 70% of organic traffic in the US related to the search for a tool for performance testing comes from JMeter, so it is still widely known and extremely popular, has many plugins and is supported for launch by various cloud platforms (for example, PFLB, Octoperf, Blazemeter, etc.) However, as application architectures evolve to include gRPC testing framework requirements, teams are exploring specialized alternatives such as a modern gRPC load testing tool to better meet performance demands.

Despite its long history of success, JMeter isn’t without drawbacks or debatable features:

Aren’t these reasons why you should look for JMeter alternatives?

Let’s take a closer look at these solutions.

List of 5 Best JMeter Alternatives for Load Testing

PFLB

PFLB is a modern performance testing tool that can follow both a developer-centric and no-code approach. It is created as a platform to help move your JMeter load testing to either the public or private cloud. Additionally, it has several vital integrations with API and user statistics platforms. It offers an advanced REST API testing platform that helps tests be created with a test builder option straight inside your browser.

Pros

• Faster test creation based on Google Analytics data.
• Seamlessly integrated with Grafana dashboards.
• Suitable for novice and experienced testers.
• Can be easily integrated with JMeter Java DSL, supporting Everything as Code paradigm.
• Faster API test creation by importing Postman and Insomnia request collections.
• AI-powered insights.
• Simple CI/CD integration.
• SLA management.
• Customizable reporting.
• Expert support.
• A wide range of protocols support.

Cons

Learn more about PFLB’s JMeter cloud load testing tool.

K6 by Grafana Labs

K6 is a one of JMeter’s alternatives, primarily aimed at developers writing in Javascript or Go. K6 users are attracted by the ability to write tests in a familiar IDE and the ease of creating scenarios. However, in need of more complex scenarios with consequently dependent requests and advanced work with data pools, including distributed testing, then the user may encounter a lack of basic functionality. As a result, there is a need to write custom code from scratch and integrate with additional external solutions, which are often available out of the box for other tools.

Pros

• The tool is tailored for developers inspired by the Everything as Code concept (see Everything as Code).
• Simple, clear, and easy-to-read Javascript scripts.
• Easy to automate the creation of scenarios.
• Well-suited for simple test scenarios (independent microservices or static websites).
• With the open load testing model, k6 based on Golang has very low resource consumption.
• There is a free version with limited functionality.

Cons

Gatling

If, until a couple or triple of years ago, Gatling was a tool for geeks who write in Scala-based DSL, the tool began to gain wider popularity after support for Java and Kotlin was added. Again, the tool is made for developers who are used to writing code, so it is most suitable for such an audience. However, as it often used to be, when product users’ amounts become more prominent, some functionality previously available in the free version has been transferred to the paid version. Of course, there are workarounds, but there is no guarantee that this will not happen again.

Pros

• The tool is designed with developers in mind, embracing the “Everything as Code” philosophy (see Everything as Code).
• Vast opportunities for creating custom code for your purposes.
• Tailored for an open load model but also suitable for a close’ one.
• Good approaches to cookie management in scripts.
• Less resource-consumptive for high RPS if scripts are written in Scala when using an open model.

Cons

Those, who love Gatling, say that the Scala programming language is simple for testing something unadvanced. Furthermore, in case of something more specific, connecting Java libraries and writing the code you need is more straightforward than implementing plugins with the JMeter class structure. But let’s be honest: plugin coverage in JMeter is still considerably higher (learn more about JMeter vs. Gatling vs. PFLB).

Locust

Locust is a tool that allows load testing to be performed by those who know one of the simplest programming languages ​​- Python. It is a relatively niche JMeter alternative, but in some cases, it can be the best solution. For example, when the team only includes people who know Python, it is inevitable that the complexity of the load-testing project is small and will definitely not increase over time.

Pros

• Very easy to use for those who know Python.
• Open source JMeter alternative.
• Easily expandable for your tasks, for example, it can be easier to work with VBS or COM/DCOM objects in Windows.

Cons

JMeter Java DSL by Abstracta

Meter Java DSL is an open-source solution that allows you to implement the Everything as Code concept, saving all Apache JMeter features underneath but considering itself as a new JMeter alternative. Old-school JMeter does not fit into the Everything As Code paradigm since scripts are created in the GUI, and its result is a JMX file in XML format, making it extremely difficult to read the code and track changes.

Therefore, the creators of this project proposed the DSL concept, which allows you to create JMeter-based scripts by writing Java code using a familiar IDE. In this approach, saving JMX files for each test is optional since they become an intermediate layer between script generation and its launch.

Pros

• A new look at the familiar JMeter with all the benefits of the Everything as Code concept.
• Suitable for Java developers.
• Solves typical JMeter problems associated with code reuse.
• Integrates with popular cloud tools that support JMeter.
• Easily extendable with JMeter plugins.
• Under the hood – the largest community among all load-testing tools.

Cons

Who Encounters the Choice of Load Testing Tools, and in What Situations?

A switch typically happens only when there’s a serious external trigger or when critical functionality is missing and becomes essential. For example, users of JMeter rarely switch away because they’re already familiar with it. This is also why LoadRunner—once the industry standard—still holds a significant market share despite its decline in popularity.

Here are the common situations where a testing department leader must choose or replace a load testing tool:

What if you find yourself needing to choose a new tool or move away from JMeter?

Fortunately, the load testing tools market is highly competitive. Each tool has its advantages and disadvantages depending on the specific situation.

For most teams, leaving JMeter aligns with the adoption of the Everything as Code concept during product transformations. As a result, alternative tools that embrace this ideology often become the primary contenders.

In essence, the consideration of alternatives to JMeter, within the framework of this concept, has two key aspects – the programming language available to the team in the current conditions and the amount of Code that will need to be written, including for the implementation of the very functionality that is not in the box.

Consider PFLB as the Best Solution as a JMeter Alternative

PFLB emerges as the best alternative to JMeter by addressing several limitations while retaining its strengths.

PFLB makes a dedicated infrastructure unnecessary by leveraging scalable and efficient cloud-based load generation for modern distributed systems, often microservices-based architecture.

The platform also offers advanced tools for sensitive data protection, ensuring your test environments remain secure while working with production-like data.

With a user-friendly interface, robust reporting capabilities, and modern API integrations for CI/CD workflows, PFLB provides a superior experience for DevOps, SRE teams, and performance engineers seeking to elevate their testing processes beyond JMeter’s capabilities.

Conclusion

Selecting the right alternative to JMeter depends on your team’s competencies, protocol support, and automation requirements. Tools like PFLB, Gatling, Locust, k6, and JMeter Java DSL offer unique strengths, such as AI-powered performance insights, diverse scripting options, and seamless CI/CD integration.

By exploring these Apache JMeter alternatives, teams can optimize load-testing processes and ensure their applications deliver exceptional performance under real-world conditions.

See also