GATLING VS BLAZEMETER
Switch to an end-to-end performance testing expert
Gatling owns its engine end to end. BlazeMeter runs JMeter, Selenium, Locust, even Gatling scripts, but it doesn't own any of them. That's the difference between an engine and a dashboard: Gatling's security, AI analysis, SLOs, and scoring are purpose-built, not bolted on top of five.
That's the real difference: not who can generate load, but who owns what happens next, how you write the test, and how much sense you can make of what it tells you.
BlazeMeter is the generalist: any engine, one dashboard. Gatling is is the specialist: one engine, built end to end.
BlazeMeter's one-dashboard cloud is a reasonable choice if your org already has scripts spread across JMeter, Selenium, Locust, or Gatling via Taurus. But running Gatling through a layer built for five engines isn't the same as running it natively, with AI, SLOs, and scoring built for Gatling alone.
BlazeMeter
Cloud-hosted JMeter, Selenium, Locust, and Gatling via Taurus. One dashboard, any engine.
Gatling Community + Gatling Enterprise
Open-source core, enterprise platform, built only for performance.
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Runs whatever you've already scripted: JMeter and Selenium natively, Locust and Gatling via Taurus.
Protocol comes coverage from JMeter, Selenium and Locust's. Broad, but bolted together from several engines.
Thread-per-virtual-user engine under the hood. Scale comes from adding more cloud machines, not from doing more per machine.
GUI-first authoring, a Chrome recorder, and no-code test builders. Approachable without a coding background.
Test-as-code in Java, JavaScript, TypeScript, Kotlin, and Scala. The same repo, build, and review flow as your app.
60,000 virtual users or 300,000 requests/second per load generator. 5M+ concurrent users on a 20-generator fleet.
HTTP/S, WebSockets, SSE, gRPC, MQTT, JMS natively, plus Kafka, AMQP, and JDBC databases via plugins.
After the run: AI analysis, SLO compliance, trends, comparisons, and a campaign score that moves over time.
What "generalist" costs you
Running five different engines means BlazeMeter can't go deep on any single one, Gatling included. Here's where that shows up.
Fixes aren't up to them
When a bug lives in the JMeter engine itself, BlazeMeter waits on the JMeter project's own release cycle, same as anyone else running it. Gatling owns the whole stack, so a fix to the engine, the reporting, or the AI layer ships on Gatling's schedule, not a dependency's.
One vertical, not one line item
BlazeMeter is one product inside Perforce's much larger testing and DevOps portfolio, alongside dozens of others. Gatling Corp has exactly one product: performance testing. No other roadmap is competing for the budget.
Load testing isn't on the roadmap
A single-vertical company ships differently. In Gatling's last release cycle we shipped an AI Assistant, an MCP server for coding agents, AI run analysis, a visual SLO builder, campaign scoring, and migration agents for JMeter and LoadRunner. Try naming a comparable list from Blazemeter.
No proprietary engine
BlazeMeter doesn't own the technology that generates your load. It runs open-source engines other people built (JMeter, Selenium, Locust, and Gatling itself via Taurus) and wraps them in a dashboard. Gatling builds and owns its engine end to end, from the socket layer up through the report.
An engine that doesn't waste a single CPU cycle
A single machine caps out around 64,000 concurrent sockets per target. Gatling’s engine is built to use nearly all of them.
