BaseRock AI vs. BlazeMeter

It is well suited for applications that are mission-critical or applications that can receive high traffic/transactions at unscheduled time periods. Using the load testing feature of BlazeMeter, we can test and ascertain the capacity of the application without the drawbacks of the usual Apache JMeter load testing which depends heavily on the host system from where the load testing is performed.

Incentivized

• BlazeMeter takes the .jmx script that teams had written for JMeter. The transition from JMeter to BlazeMeter was seamless.
• BlazeMeter offers its own cloud and hence we did not have to set it up on-premise.
• BlazeMeter hits our application from various geographic locations that simulates real life users.

Incentivized

• Blazemeter reporting is very basic and shallow. There is no way to drill down or correlate. I can get better reports by using JMeter for free.
• Blazemeter is very costly. Testing with volumes of more than 1K cu is expensive, and can be done for much cheaper if a company/team is willing to invest a bit of time to figure out how to use cloud instances and jmeter slaves, and to write a basic script to collect resulting xml output.

Incentivized

Easy to setup to do API Performance Testing. Dashboard to showcase results Capability to showcase runtime results

Incentivized

In comparison with Blazemeter the closes competitor is JMeter but it has disadvantages like it is not a tool that can be use as a collaborative tool and works locally in a computer, Blazemeter is in the web so different people can access and run tests or collaborate do add, edit or delete the existent scripts.

Incentivized

• It helped positively by helping to identify the maximum capacity needed for high traffic periods
• Saved revenue by eliminating unwanted duplication of systems

Incentivized