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Top 5 JMeter Alternatives

Dec 20, 2024
6 min read

By Boris Seleznev, updated December 20, 2024.

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Author

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.

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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.

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.)

organic traffic for different load testing tools

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

  • You can’t create load tests like Code in CLI without additional add-ons (such as JMeter Java DSL from Abstracta).
  • When generating tens or hundreds of thousands of RPS, JMeter can be less resource-efficient compared to competitors.
  • Its standard distributed load testing can produce unnecessary parasitic traffic, which may affect test metrics.
  • The user interface feels outdated and legacy.
  • It was originally designed for a closed workload model and still only has experimental support for open workload models.
  • JMeter is not a browser, meaning you cannot get frontend performance metrics during testing.

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

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

In most cases
Teams stick with a load testing tool they start using early on.

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:

  • 01
    New technology in the stack requires testing: Current tools may not support specific technologies like gRPC streaming calls, WebRTC, or IVR telephony.
  • 02
    Scaling up a growing product: When startups begin scaling, business forecasts may indicate a significant increase in load. Often, there’s a lack of in-house expertise, so selecting a core tool around which load testing practices are built becomes necessary.
  • 03
    Team composition changes: New team members may have prior experience with other tools. It’s often easier to implement something they know than to learn an unfamiliar tool.
  • 04
    Tool unification in large companies: As part of digital or product transformation, companies may unify testing tools, assigning load testing responsibilities to development teams under the Everything as Code framework.
  • 05
    Transition to the cloud: If load testing moves to a cloud environment (private or public), existing tools may not be compatible with the cloud solution.
  • 06
    Emergence of new, more effective tools: Technological advancements may introduce better solutions for regular load testing.

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.

Everything as Code

Everything as Code (EaC) is a concept where code and version control systems manage and automate processes throughout the development lifecycle. Load testing is no exception to this trend.

Advantages of Everything as Code:
Customizability: Easily expand tool capabilities by writing custom code.
Developer-friendly: Makes load testing manageable and convenient for developers.
Familiar workflow: Tests can be created within a familiar IDE.
Code reuse: Simplifies the reuse of test scripts and components.
Improved script clarity: Enhances the team’s understanding of scripts.


Challenges of Everything as Code:
High programming skills required: Teams need strong competencies in the programming language used to write test scripts.
Resistance from developers: If the company follows a service-based approach to load testing—where application developers believe someone else should handle it—implementing this concept can be challenging.


A visual diagram could illustrate the complexity of choosing load testing tools, considering factors such as programming languages, traditional tools (“old school”), Everything as Code concepts, and supporting features.
choosing load testing tool jmeter alternatives

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.

Let’s take a closer look at these solutions.

List of 5 Best JMeter Alternatives for Load Testing

PFLB

PFLB - the Best Performance Testing Tool to Identify Performance Bottlenecks

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, helping 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

  • The free plan has evident limitations.
  • No APM integration.

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

Start FREE Load Testing with PFLB

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K6 by Grafana Labs

grafana labs logo

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

  • QA teams are not accustomed to testing in the Everything as Code style and need time to learn and restructure their thinking.
  • Advanced work with data pools requires additional tricks, external solutions, and custom development.
  • With large scenarios and data pools, memory leaks can occur there when other toolkits do well.
  • Limitations when working with initialization modules.
  • Sometimes, there are problems when translating Javascript code into Go due to the large difference in language paradigms.
  • When changing the tool, be prepared to automate again.
  • The concept of “some testing is better than none” promoted by the product team carries methodological risks.
  • The tool is evolving towards browser-level testing, ignoring the development of the core for protocol-level testing.
  • Some protocols, although not the most frequently tested, are not supported out of the box.

Gatling

Gatling - the Load Testing Solution

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

  • Sending metrics to an external source has become a paid service; you must write your sending mechanisms or find external solutions for free use.
  • No distributed testing in the free version.
  • Bad reviews from specialists on using the recorder.
  • The debugging process has evident problems.
  • The Scala-based DSL may be challenging for testers without a programming background.
  • The Gatling community often has only common answers; deep-digging should be done on your own, especially when you don’t use Scala.
  • Some less commonly tested protocols are not inherently supported by default.

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.

Locust

Locust - JMeter alternative open source

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

  • Small community.
  • Python, as an interpreted language, supports only an open load model (no async requests, context switches between, only single-threaded load testing).
  • Not suitable for tasks that use CPU heavily without implementing distributed testing.
  • No recorder, tests are collected manually.
  • Supports only the most basic protocols.
  • Managing a large number of locust files for distributed testing and complex scenarios can begin to be a headache.
  • When doing distributed testing, you need to monitor your load stations’ resource consumption carefully.

JMeter Java DSL by Abstracta

 alternative jmeter DSL

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

  • Somewhat inferior to competitors in resource requirements for large distributed loads.
  • Still hard to start for testers without programming skills.

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.

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

See also

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