n8n vs Activepieces
Two of the top projects in Workflow automation with AI, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
n8n
Visual workflow automation with AI agent nodes and 1500+ integrations
Activepieces
Self-hosted workflow automation with TypeScript integrations, alternative to Zapier
Verdict
n8n ranks higher, 95 to 82. Of the 4 score parts we measure for both, n8n leads on 2, Activepieces on 1 and 1 is even.
- Adoptionn8n leads by 40 points, 100 to 60: a wide gap.
- FreshnessEven at 100.
- Maintenancen8n leads by 6 points, 92 to 86.
- Agent-readyActivepieces leads by 15 points, 85 to 70: a wide gap.
Pick n8n if you are
Teams wiring LLMs and agents into existing SaaS tools, self-hosted or cloud
- 1500+ integrations and 9,000+ templates cover most common SaaS wiring
- Visual canvas with JavaScript, Python and npm code when needed
Pick Activepieces if you are
Teams self-hosting Zapier-style automation with LLM and MCP integrations
- 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
| What we compare | n8n | Activepieces |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 100, widely used | 60, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 92, healthy | 86, healthy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 208.5k | 25.2k |
| License | custom license (read the license) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | TypeScript | TypeScript |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
n8n
n8n is a node-based canvas for building workflows and multi-step AI agents, with JavaScript, Python and npm packages usable inside nodes. It connects to OpenAI, Anthropic, Google and open-source models, and lists 1500+ integrations and 9,000+ workflow templates. It runs self-hosted or on n8n Cloud, under the Sustainable Use License rather than an OSI license.
Who it is for: Teams wiring LLMs and agents into existing SaaS tools, self-hosted or cloud
Strengths
- 1500+ integrations and 9,000+ templates cover most common SaaS wiring
- Visual canvas with JavaScript, Python and npm code when needed
- Model-agnostic: OpenAI, Anthropic, Google or open-source models
- Supports human approvals and observability for multi-step AI workflows
Weaknesses
- Fair-code Sustainable Use License, not OSI open source; use is restricted
- Role-based access and audit trails fall under the Enterprise License
- RAM and CPU requirements are not stated in the README
- Documented quick start requires Docker
- no GPU
- Needs Docker
- 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
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