NeoLoad vs Locust
Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.
Entry price
Quote on request
Quote onlyFree and open source
Open sourceWhat drives the bill
The metric that actually scales your invoice.
Enterprise licensing by peak virtual users, negotiated annually.
Free and open source. You pay in engineering time and CI minutes.
Free tier
Free edition limited to a small number of virtual users.
Everything, self-hosted
Open source
MIT
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Established
Tricentis · since 2005
Widely used
OSS community · since 2011
Strengths
- Handles enterprise protocols such as SAP GUI and Citrix that open-source tools cannot.
- APM correlation makes root-cause analysis much faster than latency graphs alone.
- Both GUI design and as-code authoring, so mixed-skill teams can share a suite.
- Test scenarios are plain Python, so any logic is expressible without workarounds.
- Distributed mode is conceptually simple and works well on Kubernetes.
- Live web UI is useful during an exploratory ramp-up.
Limitations
- Expensive, with a procurement-scale sales process.
- Overkill for a straightforward web or API workload.
- Proprietary scripts do not port to other tools.
- Python's per-user overhead is higher than k6 or Gatling; big loads need more machines.
- Reporting is basic — plan on exporting to Grafana.
- HTTP-centric; other protocols require writing your own client.
Best for
Large enterprises performance-testing SAP, Citrix or Oracle estates.
Python teams who want load scenarios expressed in their own language.
Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.