So much mental and technical effort goes into developing applications and software. Unfortunately, unless you are building exclusively for yourself or a few people, it is important to see how your creation holds up with thousands of users before a public release.
That is where performance testing comes in – as an aspect in the development cycle for evaluating your application’s stability, responsiveness, and speed under load.
There are different tools for various aspects of performance testing including spike, stress, endurance, and volume testing. However, when it comes to load testing, Gatling and JMeter have emerged as the dominant options for developers.
They help engineers run load tests for different sets of applications, including APIs, internal and external web applications, and websites. Both are excellent at what they do, which is why it can be hard to choose which one is better.
I answer that question in this article by comparing Gatling and JMeter across different performance categories. At the end of it, you will have a solid idea of the most efficient tool for your team.
Ready? Let’s ride.
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Considering the importance of performance testing in software development, it is no surprise that two of the most popular load testing tools are open source. Gatling is an open-source load and performance software written in Akka, Netty, and Scala.
The tool enables developers to create and run high-performance and manageable load tests. It offers plenty of support for different aspects of performance testing. Also, because it is Scala-based, it can run on any system, local machine, or cloud server.
It went live for the first time on January 13, 2012, before Stephane Landelle started an eponymously named company in service of its development in July 2015. Since then, it has grown in popularity, achieving more than 800,000 downloads in August 2017.
Gatling is especially popular among engineers because it allows them to write performance tests as source code. The implication is it is possible to save your tests under version control systems like GitHub and GitLab. It also means you can collaborate during test designs and easily track changes over time.
Besides that, it is also compatible with Continuous Integration (CI) pipelines. This feature enables the complete automation of performance testing during the software development process.
Apache JMeter, otherwise known as JMeter, is one of the software projects supported by the Apache Software Foundation. Like Gatling, it is also an open-source software distributed under the Apache License, and it has been around since 1998. Simply put, it is one of the oldest performance tools in the world.
Besides being older and more mature, JMeter is also written entirely in Java. Well mostly. According to OpenHub, there are parts of it that contain XML and HTML. The source code is available to anyone for modification and customizations according to their needs.
Speaking of the source code, it has a large codebase with more than 500k lines. It has recorded over 105 releases and 15,700 commits to date, meaning it has an active user base.
It measures relevant metrics for FTP applications, web applications, and HTTP back-end servers. Others include JMS, LDAP, and different TCP connections.
Developers can simulate heavy loads on a server and perform functional and non-functional tests like stress and web service testing.
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Both tools’ level of protocol support is an important metric when considering which load testing tool is right for you. It informs the range of programs and applications that you can test for.
Here is how they both compare in this regard.
Out of the box, Gatling supports a shorter list of protocols compared to JMeter. It officially supports HTTP, WebSockets, Server-sent events, and JMS (Java Message Service).
Its HTTP support is particularly one of the best on the market due to the extra attention given to it by the development team.
Gatling’s HTTP protocol support allows you to load test web applications, web services, and websites. This support extends to HTTPS too. You can use it to test different browser features like redirecting, caching, and cookies.
Its support for JMS also makes it an ideal tool for testing web chat communication or any other feature that needs asynchronous delivery of messages.
Aside from the out-of-the-box list of protocols, Gatling can also implement additional protocols due to modifications from its open-source community.
These protocols include ZeroMQ, MQTT, Advanced Message Queuing Protocol (AMQP), among several others. All you have to do is manually add a line of code to enable support for each protocol.
Unsurprisingly, the older performance testing tool comes with a lot more protocol support out of the box. Its list of in-built protocol support on various server types and their uses include —
- HTTP and HTTPS – for browser-based web apps and websites
- JDBC – for testing database connections
- POP3, IMAP, SMTP – for testing email services
- FTP – for file transfer applications
- LDAP – testing directories
- JMS – Messaging oriented services
This is by no means an exhaustive list of every protocol supported by JMeter, but you get the idea. As you can see, it supports more than 69% of the protocol demand across web applications, web services, and mobile apps.
This generality makes it an ideal performance testing tool for any enterprise.
JMeter wins this category. Despite Gatling’s excellent support for HTTP(S), JMeter’s broader protocol support makes it a better choice.
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Most applications have concurrent users, so it is vital to know how they will perform under this scenario before public release. Distributed testing, one of the software testing strategies, is one way to test for this.
Let’s find out which tool is better at this.
Distributed testing means using multiple computers (slaves) as load generators. As shown by the image above, the premise is to share the load with different devices to simulate concurrent users.
JMeter is designed perfectly for this. Its architecture involves the connection of slaves (irrespective of their number) to the master machine via the RMI protocol. Once connected, the master machine then uses JMeter to simulate each slave.
For example, suppose you have ten slave machines, and you program the JMeter script to simulate 1000 users. Your total simulation using this distributed system will be 10,000 users. In other words, you can load test an endless amount of users with limited hardware resources.
Retrieving the result is also easy. Results from every slave machine return to the master machine for collation and consolidation.
Gatling, on the other hand, is a single host. It means even though the tool is written in Akka, a toolkit for the construction of distributed applications, the open-source load testing tool does not support distributed load testing.
As a result, it is impossible to use it to scale testing horizontally. There are a couple of workarounds for this, but none of them come out of the box. One of them is launching multiple Gatling simulations on many machines at the same time.
The process is entirely manual and hardware intensive. Furthermore, you will have to consolidate results from the various injectors manually.
However, the tool’s commercial version, Gatling Enterprise, has a distributed testing feature called Cluster Mode. It allows you to deploy multiple injectors on-premises or via the cloud.
Because it is free and has out-of-the-box support for distributed testing, JMeter fully edges out Gatling in this category.
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What is the process of executing code and analyzing the expected and actual results? Here is how Gatling and JMeter compare when it comes to test execution.
One fundamental difference between Gatling and JMeter is that the former is designed specifically for developers. Users run tests by typing lines of code. So, to run a load test with Gatling, you have to run the .sh script and select the simulation you want to run within the simulations folder.
While Gatling runs the simulation, it shows the statistics within the console and the final result is viewable at the end of the test in a static HTML report.
Gatling’s test report consists of metrics like response time and the number of OK/KO transactions. These detailed statistics are shown for every request. However, the available metrics are non-customizable.
To make up for that limitation, Gatling supports integration with external analysis tools. You can plug it with Grafana with InfluxDB, Graphite.
JMeter still lends itself for use by non-technical testers, so it offers the ability to launch a test via a GUI. The other method, launching a test via the command line, is available for developers who prefer typing code.
The variety in the test execution process goes beyond launching tests with JMeter. It also offers different means of viewing results with its GUI feature. It is possible to view results as a table or a graph, as shown above.
The unfortunate downside of this method is that GUI listeners consume a lot of memory, limiting your testing capacity. For optimal testing, it is better to launch using the command line and save your results as JTL files.
Still, your choices are not limited to graphs and JTL files. The JMeter 3.0 release made HTML Reports available.
As for the performance metrics in the report, JMeter offers several, and they include –
- Response times over time
- Error table (summary of all errors and proportion to total request)
- Statistics table summarizing all metrics per transaction
There are more, but JMeter supports BackendListener. You can use it to export your results to Grafana or InfluxDB for a more detailed analysis.
Although it comes with its disadvantages and performs similarly during test execution, JMeter’s GUI feature expands the usability. It also offers a lot more details in its results. JMeter wins.
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Executing a test and getting back the results is nice. It is even better to have real-time test monitoring of script behavior. Here are the features offered by each tool as solutions.
JMeter has a GUI that allows you to monitor the results of your test in real-time. However, as mentioned in the previous category, it requires using GUI JMeter listeners and eats up a lot of memory.
Users can save their performance tests as a script and run them in non-GUI mode via the command line to solve this problem.
QA engineers and developers can then use the script for real-time monitoring using the Out-of-the-Box Logs. With it, you can track basic metrics like –
- Average throughput
- Average response time
- Minimum and maximum response time
- Number of active users
- Total number of started threads
- Total number of finished threads
It is also possible to integrate JMeter with Grafana, which means access to additional performance metrics during live monitoring. However, the installation process can be complicated because it requires configuring a separate plugin.
In contrast, Gatling provides live feedback by default via its console output. There is no significant impact on memory while you track different script execution metrics. The available data points are enough for developers and QA engineers to get a clear picture of script behavior.
But they are not as comprehensive or configurable as they can or should be. For more detailed real-time monitoring, Gatling has Enterprise, a management interface available in its commercial version. It has advanced metrics and features, among other features like out-of-the-box MQTT support.
In the open-source version, Gatling built functionality into the tool, allowing easy integration with Grafana. With it, you can monitor your script behavior in real-time via a dashboard with more extensive data points.
Gatling’s real-time monitoring features, at default, offer additional information about script behavior. It is also easier to integrate it with Grafana for customizable and meticulous monitoring.
How much third-party integration do Gatling and JMeter support for services and applications that are not inbuilt? How easy is it to integrate with them? Here is a quick breakdown.
Most developers who use Gatling use it as a continuous load testing tool. Thus, the tool’s in-built features are enough and do not require any third-party add-ons or plugins to serve its purpose.
Still, as mentioned a couple of times earlier, Gatling supports several official and community plugins. You can integrate the load testing tool with —
- Integrated development environments (IDE) like IntelliJ IDEA and Eclipse
- Build tools like SBT and Apache Maven
- Apache Cassandra
- Apache Kafka
- And more
Besides extending its functionality with plugins, Gatling also has Continuous Integration support, enabling automated load testing. It integrates with CI/CD tools like Jenkins and Hudson and is often used in DevOps organizations.
As for the integration process, users can add most plugins to Gatling with a few lines of code.
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JMeter, out of the box, comes with several features and supports multiple protocols. However, due to years of development and its open-source status, many third-party plugins are available for extending its capabilities.
There is a dedicated JMeter Plugins website that collates a list of integrative plugins. As of the writing of this article, you can search through 93 plugins. These include three Basic Graphs, Inter-Thread Communication, Flexible File Writer, and Custom Thread Groups.
Installing them is also very easy. All you have to do is install the Plugins Manager from the website. Then using its UI, you can install other plugins automatically instead of doing so manually. You can also use it to upgrade or uninstall each plugin.
A draw. Both load testing tools offer plenty of plugin support and an easy way to integrate them.
How approachable are these tools for new users? Are they suitable for regular use? Here is how both software hold up when it comes to usage.
Apache JMeter’s GUI tool already ensures that users with limited coding expertise can still run tests with it. Although it lacks a stylish design, the GUI tool makes it easy to use, allowing users to set up performance tests using a point and click method.
Its support for distributed testing also makes it a simple option for simulating millions of users.
More importantly, learning JMeter is a breezy endeavor. The load testing tool comes with excellent documentation. Every feature has a detailed explanation for every setting, along with helpful information like Best Practices, Change History, FAQ, and JMeter Wiki.
By simply studying the documentation, you can learn how it works and how to create your first test.
The absence of a GUI makes Gatling harder to use. Setting up a test involves coding. However, that is only an issue to the extent where some team members are non-developers.
Gatling’s command-line or Non-GUI mode could even be considered a welcome development if all members are technically savvy.
Additionally, because it uses Scala as its scripting language, Gatling can work on most hardware, if not all. It runs on the Java platform and is compatible with any Java-based library.
Other than being easy to use, Gatling is also simple to learn. It has clear and understandable documentation that explains every feature in-depth for the free and paid versions. It also includes valuable guides on installation and issue tracking, along with tutorials.
Another draw. Both tools are easy to use for their respective target users, and they come with excellent documentation that aids mastery.
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Error fixing? Feature updates? The final category is the reliability of either tool for long-term use.
Gatling is an open-source load and performance testing tool, so its codebase is available to anyone who wishes to make changes. However, that might not be necessary because it has an active community that frequently contributes to its development.
The company behind its development, Gatling Corp, releases a version every year, and its GitHub page has more than 60 known contributors.
In terms of support, it has a substantial user base. Thus, there are plenty of articles and tutorials online should you ever need help.
Having maintained relevance since its first release in 1998, JMeter has established its long-term reliability. But it is not resting on its laurels either. The performance testing tool has an active and large user base.
Its GitHub page has over 42 contributors and has recorded more than 17,420 commits and 105 releases to date. There is also a robust support and training system available for free on the internet. They are available in different forms, including blogs, tutorial videos, and online courses.
Overall, there is practically no JMeter issue that you can’t solve with a quick Google search.
Both of them have a dependable support system, but the final round goes to JMeter. Thanks to its long history, it has a deeper pool of online knowledge and a more active community.
- Both of them support non-functional tests such as stress and web service testing
- Both have clear, understandable, and extensive documentation
- Both are open source and distributable under the Apache 2.0 license
- Both require Java JRE installed on the machine for setup
- Gatling and JMeter have built-in HTTP Proxy Recorders
- JMeter supports distributed testing. Only Gatling Enterprise does
- JMeter uses One Thread = One User paradigm or Synchronous processing. Gatling uses an asynchronous thread model
- JMeter is GUI oriented. Gatling is completely code-based
- JMeter supports multiple protocols out of the box. Gatling only supports HTTP, WebSockets, JMS, and MQTT
- JMeter was developed exclusively in Java, while Gatling was written in Scala.
- Offers integration into CI/CD pipelines
- It needs fewer third party plugins
- Lightweight and consumes smaller memory
- Has recording functionality
- Offers real-time test monitoring
- Has a smaller open source community
- No GUI for non-developers
- Has GUI for less technical users
- It has a long list of supported protocols and plugins
- Completely open-source and free
- Plenty of online support
- Offers dynamic HTML reports
- It consumes a lot more memory
- Not ideal for software configuration management (SCM)
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As shown so far, both are excellent at what they do and are deployable in service of different applications and infrastructure.
However, JMeter beats Gatling thanks to features like distributed testing and its online community.
The ability to test for millions of users from one machine and the prospect of omnipresent support from its large user base makes Apache JMeter the better choice.
Scott L. Macarthur is a marketing consultant and an online author. He is mostly engaged in providing his expertise to startups and SMBs. He is also an author on TheNextWeb.