n8n vs Activepieces
Two of the top workflow automation with ai, side by side: score, setup, license, activity and what each review found.
n8n
Visual workflow automation with code steps, AI agent nodes and 1500+ integrations
Activepieces
Self-hosted workflow automation with TypeScript integrations, alternative to Zapier
| What we compare | n8n | Activepieces |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 99, widely used | 27, niche |
| Freshness | 100, active | 100, active |
| Maintenance | 92, healthy | 86, healthy |
| Easy to run | 33, some setup | 50, easy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 207k | 25k |
| License | custom license (read the license) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Not stated | TypeScript |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
n8n
n8n is a fair-code workflow platform that runs as one Docker container (docker.n8n.io/n8nio/n8n, port 5678) and combines a visual canvas with JavaScript, Python and npm code nodes. AI agent and workflow nodes connect to OpenAI, Anthropic, Google or open-source models, with human-approval steps and observability, and 1500+ integrations plus 9,000+ templates cover the rest of the stack.
Who it is for: Teams automating business workflows that include LLM steps
Strengths
- 1500+ integrations and 9,000+ ready-made workflow templates
- Code nodes run JavaScript or Python and can pull npm packages
- Single container on port 5678 with one data volume
- Switch model providers without rebuilding the workflow
Weaknesses
- Sustainable Use License (fair-code, source-available), not an OSI license
- Some features require a separate n8n Enterprise License
- README states no database, RAM or CPU requirements
- no GPU
- Models: OpenAI, Anthropic, Google, open-source models
- port 5678
Activepieces
Activepieces is a no-code workflow builder with loops, branches, auto retries, HTTP calls and npm-backed code steps, and flows are versioned. Integrations are called pieces: TypeScript npm packages, 280+ of which are exposed as MCP servers for Claude Desktop, Cursor or Windsurf. It also has AI pieces for several providers, human-in-the-loop approvals, and chat and form triggers.
Who it is for: Teams self-hosting Zapier-style automation with LLM and MCP integrations
Strengths
- Pieces are open-source TypeScript npm packages with hot reloading for local development
- 280+ pieces usable as MCP servers from Claude Desktop, Cursor or Windsurf
- Flows are versioned and support loops, branches and auto retries
- Built-in approval, delay, chat and form triggers for human-in-the-loop flows
Weaknesses
- Enterprise features sit under a separate commercial license, not MIT
- README does not state RAM, CPU or database requirements
- Automation-first; AI agents are one feature rather than the core design
- README claims of 200+ and 280+ pieces are inconsistent
- no GPU
- Docker + Compose
- Compose runs PostgreSQL, Redis
- Models: OpenAI