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Gatling vs. JMeter: What Tool to Use?

Mar 20, 2025
7 min read
author denis sautin preview

Denis Sautin

Author

Denis Sautin

Denis Sautin is an experienced Product Marketing Specialist at PFLB. He focuses on understanding customer needs to ensure PFLB’s offerings resonate with you. Denis closely collaborates with product, engineering, and sales teams to provide you with the best experience through content, our solutions, and your personal journey on our website.

Product Marketing Specialist

Reviewed by Boris Seleznev

boris author

Reviewed by

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.

Imagine launching a new product, only to have your website crash the moment traffic spikes. Or rolling out an update, confident in its stability — until real users start complaining about slow response times and timeouts. Performance issues can make or break an application, and that’s why performance testing is non-negotiable. Many development teams are discovering the benefits of continuous performance testing to catch these issues early, preventing costly failures in production.

Now, the question is: What’s the best tool for load testing? 

There’s no shortage of options, but two names stand out:

  1. 1.
    JMeter – A well-established, open-source tool with broad protocol support.
  2. 2.
    Gatling – A developer-friendly, high-performance framework built for automation.

Both tools has its strengths and trade-offs. But if you’re wondering which one fits your team’s workflow, technical expertise, and performance testing needs, this guide will break it all down for you.

Performance testing tools come in different flavors, each catering to specific use cases, technical expertise, and scalability needs. Modern approaches often emphasize continuous delivery performance testing to ensure reliability throughout development. Let’s compare the tools to understand what they bring to the table.

What is JMeter?

pflb-jmeter-integration-logo

JMeter is one of the most well-known open-source performance testing tools, developed by the Apache Foundation. It has been around for years and remains a go-to solution for testing web applications, APIs, databases, and various other services.

  • Protocol Support
    One of JMeter’s biggest strengths is its ability to handle a wide range of protocols beyond just HTTP, including FTP, JDBC (databases), JMS (messaging), SOAP (web services), and TCP. This makes it a versatile tool for enterprises dealing with complex system architectures.
  • GUI-Based Design
    JMeter provides a graphical user interface (GUI) that allows testers to design test cases without deep programming knowledge. While scripting is optional, advanced users can enhance tests with Groovy or Java-based scripting for custom logic.
  • Scalability & Load Testing
    JMeter can simulate thousands of concurrent users but relies on thread-based execution, meaning high loads require distributed testing setups across multiple machines. Without proper tuning, JMeter can be resource-intensive, especially for large-scale tests.

Best For: Teams that need an open-source, highly extensible tool for multi-protocol testing, provided they’re comfortable with manual configuration and infrastructure setup.

For teams looking to avoid the complexity of setting up and maintaining infrastructure manually, exploring options like running JMeter tests in the cloud can significantly reduce overhead and improve scalability. Meanwhile, those focused on backend robustness, especially in microservices or complex API ecosystems, leveraging advanced methods to ensure API stability under load becomes essential to validate performance under real-world conditions.

What is Gatling?

Gatling - the Load Testing Solution

Gatling is a developer-centric performance testing framework designed for modern web applications. Unlike JMeter, which provides a GUI, Gatling is entirely code-driven, meaning tests can be written as Scala, Kotlin, Java and JavaScript code.

  • High-Efficiency Load Generation
    Gatling’s non-blocking, asynchronous architecture allows it to simulate high concurrency with minimal resource consumption. This makes it far more efficient than thread-based tools like JMeter, enabling large-scale load tests on fewer machines.
  • Web & API Focused
    Gatling supports HTTP(S), WebSockets, JMS (messaging systems), and SSE (server-sent events) but lacks built-in support for FTP, JDBC, SMTP, or SOAP. This makes it ideal for testing web applications and APIs but less flexible than JMeter for broader protocol testing.
  • CI/CD Integration
    Designed with automation in mind, Gatling fits seamlessly into DevOps workflows, working well with Maven, Gradle, and Jenkins. This makes it a solid choice for continuous performance testing during development.

Best For: Developers and DevOps teams who prefer a “load testing as code” approach, need high-performance test execution, and want to integrate performance testing directly into CI/CD pipelines. Learn more about Gatling alternatives in our article.

JMeter vs Gatling: Comparison Table

How does Apache JMeter compare to Gatling for load testing? Check out the JMeter and Gatling comparison below:

AspectApache JMeterGatling (Open Source)
License/CostOpen-source, free to use. No licensing cost, but users must provision and maintain their own infrastructure.Open-source (free) core engine. Gatling Enterprise (paid) available for additional features and support.
Test Design ApproachGUI-driven test plan creation. Supports HTTP recording and scripting in Groovy/Java for advanced logic.Code-based DSL for test scenarios (Scala/Java/Kotlin). No built-in GUI, but a Recorder can generate scripts from user flows.
Supported ProtocolsBroad protocol support: HTTP/HTTPS, FTP, JDBC, SOAP, REST, JMS, SMTP, POP3, IMAP, LDAP, TCP, and more. Extensible via plugins.Primarily web-focused: HTTP/HTTPS, WebSockets, JMS, and SSE. Does not natively support databases, FTP, or email testing without additional code.
Extensibility & CustomizationHighly extensible via plugins and scripting. Large community contributing extra protocols, graphs, and functions.Supports custom protocol implementations via code. Can integrate with external libraries but has fewer ready-made plugins.
ScalabilitySupports distributed testing, but users must manually set up and maintain load generators. Cloud scaling is possible via third-party services.Efficient load generation using asynchronous architecture. For extremely large tests, manual distribution or Gatling Enterprise for clustering.
Reporting & ResultsBasic reports in GUI with a CLI report generator. Supports CSV/XML exports and integration with external tools like Grafana for real-time monitoring.Generates automatic HTML reports with detailed performance metrics. Open-source version lacks live monitoring, requiring external metric push for real-time tracking.
CI/CD & AutomationSupports automation via CLI. Can integrate into CI/CD pipelines (Jenkins, Azure DevOps, GitLab CI) but requires additional setup and maintenance.Designed for CI/CD. Simulations are written in code, making it easy to integrate with Jenkins, Maven, and Gradle for automated performance testing.
Ease of UseMedium – GUI helps with basic tests but complex scenarios require scripting. Setting up distributed tests can be time-consuming.High for developers, as the code-based approach is structured and efficient. Low for non-programmers due to the requirement to write and maintain Scala scripts.
Ideal Use CasesComprehensive performance testing where multiple protocols are needed, especially for enterprises with experienced performance engineers. Suitable for teams that can fine-tune infrastructure and configurations.Best for continuous performance testing in development/DevOps environments. Great for stress-testing high-traffic services efficiently and integrating with CI/CD pipelines. Works well when teams have coding expertise.

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What Are The Key Differences Between JMeter and Gatling?

Every performance testing tool has its strengths and trade-offs. Let’s explore Gatling vs Jmeter comparison in more detail:

JMeter: Pros and Cons

One of the key Apache Jmeter and Gatling differences is that JMeter is a go-to open-source solution for performance testing, widely used in enterprise environments. It’s flexible but comes with notable challenges. Learn more about JMeter alternatives.

✅ Pros:

  • Free and open-source – No licensing costs, making it accessible to all teams.
  • Broad protocol support – Works with HTTP(S), FTP, JDBC, JMS, SOAP, REST, SMTP, LDAP, and more, making it ideal for testing complex system architectures.
  • Highly extensible – Large plugin ecosystem and support for scripting (Groovy, Java, JSR223) allow customization for advanced scenarios.
  • Integration-ready – Works with Jenkins, GitLab CI/CD, InfluxDB, Grafana, and other monitoring tools for test execution and reporting.

❌ Cons:

  • High memory consumption for large-scale tests – Uses a thread-based approach, requiring multiple machines for massive loads.
  • No real browser execution – JMeter sends HTTP requests but does not execute JavaScript, making it harder to test modern dynamic web applications.
  • Requires manual setup – Distributed load testing involves configuring multiple instances manually, which can be time-consuming.
  • Outdated GUI – While functional, JMeter’s interface feels clunky compared to modern tools, leading to a steeper learning curve for beginners.

Gatling: Pros and Cons

Gatling is a high-performance testing framework designed for developers and DevOps teams. It excels in efficiency and automation, but its code-driven approach limits accessibility.

✅ Pros:

  • Lightweight and scalable – Uses asynchronous non-blocking IO, enabling it to simulate high user loads with minimal resource consumption.
  • Great for CI/CD – Designed to fit seamlessly into DevOps workflows, making it ideal for continuous performance testing.
  • Rich reporting – Generates detailed HTML reports with response time distributions, error rates, and percentiles.
  • Good scripting capabilities – Written in Scala, Kotlin, Java and JavaScript, allowing for precise control over test scenarios.
  • Efficient for high-traffic services – Gatling’s architecture allows it to handle thousands of virtual users per instance, reducing hardware needs.

❌ Cons:

  • Requires programming knowledge – Tests are written in Scala (or Java/Kotlin), which creates a steep learning curve for non-developers.
  • No built-in GUI – Unlike JMeter or PFLB, Gatling lacks a native graphical test builder, meaning users must define test flows entirely in code.
  • Limited protocol support – Primarily supports HTTP(S), WebSockets, JMS, and SSE, making it less versatile than JMeter for database, email, or FTP testing.
  • Scaling requires manual setup – While efficient, running tests across multiple machines requires Gatling Enterprise or manual orchestration.

What If Neither Is For You?

PFLB - the Best Load Testing Tool to Identify Performance Bottlenecks

If neither Gatling nor Locust fits you needs — consider PFLB. PFLB is a next-generation, cloud-based performance testing platform that takes a radically different approach from traditional tools like JMeter and Gatling. Instead of requiring complex scripting or infrastructure setup, PFLB provides an easy-to-use, AI-powered environment for large-scale performance testing.

  • No-Code Test Creation
    Unlike JMeter or Gatling, PFLB allows users to design load tests without any coding or scripting. Its drag-and-drop UI makes it accessible for testers, developers, and even non-technical teams—while also supporting integrations like secure data masking for compliance and testing, which ensures that sensitive information remains protected throughout test cycles.
  • Cloud-Based Scalability
    While JMeter and Gatling require manual setup for distributed testing, PFLB runs entirely in the cloud, allowing users to simulate millions of virtual users across multiple geographic locations instantly. No hardware provisioning or setup is needed.
  • AI-Powered Performance Insights
    PFLB doesn’t just execute load tests—it analyzes results in real-time using AI to identify bottlenecks, trends, and potential system weaknesses before they become real-world problems.
  • Modern Protocol Support
    In addition to HTTP(S), PFLB supports gRPC (used in microservices), Kafka (streaming data services), AMQP/JMS (messaging queues), and REST APIs, making it ideal for modern cloud-native applications.

Best For: Enterprises and teams that want fast, scalable, and effort

Final Thoughts

Looking closely at JMeter vs Gatling you can see that traditional performance testing tools still have their place, but they come with trade-offs—whether it’s complex setup, scripting requirements, or infrastructure limitations. They work well if you have a dedicated team of engineers ready to fine-tune and maintain your testing environment. But for businesses that need scalability, efficiency, and real-time insights without the hassle, PFLB is the smarter choice.

With cloud-based scalability, AI-driven analysis, and a no-code interface, PFLB removes technical barriers while delivering enterprise-level performance testing. Whether you’re simulating millions of users, running continuous CI/CD tests, or preparing for a high-traffic event, it provides everything you need without the complexity.

If performance testing should be seamless, scalable, and insightful — PFLB is the way forward.

Ready to Get Started with Load Testing?

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