n8n vs Activepieces: Open-Source Automation Head to Head
n8n
Open-source workflow automation with native AI nodes and full self-hosting support.
Activepieces
Open-source workflow automation with credit-based cloud pricing
Verdicts by Task
Native AI nodes and agent patterns are production-proven; Activepieces is still building this muscle.
Mind the n8n 2.0 upgrade — community nodes need 2.0-compatible releases before you migrate.
MIT-licensed core passes OSS policy reviews that n8n's fair-code license fails.
Verify the specific pieces you need are in the MIT core, not the enterprise edition.
Queue mode, workers, and a larger operational knowledge base make scaling predictable.
Activepieces is closing the gap release by release — revisit if their roadmap lands.
Feature Comparison
| Dimension | n8n | Activepieces |
|---|---|---|
| AI-native | AI-Powered | AI-Powered |
| Self-hosting | Mature: Docker, Kubernetes, queue mode for scale | Solid Docker story; fewer battle-tested scale patterns |
| AI capabilities | Native AI nodes, agent workflows, LangChain integration | AI pieces available but the catalog is thinner |
| Integration library | 500+ nodes plus community catalog (verify 2.0 compatibility) | Growing piece library; easier piece-authoring framework |
| License | Fair-code (Sustainable Use License) — restrictions on commercial hosting | MIT core — genuinely open source |
| Ease of use | Developer-leaning; powerful but denser UI | Cleaner non-technical builder experience |
n8n wins for production-grade self-hosting
n8n wins decisively on AI workflow depth
n8n wins on count; Activepieces wins on contribution ease
Activepieces wins for teams with strict OSS-license policies
Activepieces wins for mixed technical/non-technical teams
Still deciding between these two?
Choosing is the easy part. Getting it running inside your business, on your data, with your team using it, is the work. We do both.
The conversation runs on Gnosari, one of the tools in this directory. A real conversation, not a sales script.