Activepieces vs n8n

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-29
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At a glance

DimensionActivepiecesn8n
Pricing modelFreemium; SSO, audit logs, SCIM are paid tiersFreemium; SSO and audit logging start at the €667/mo Business tier
Integration catalog760+ open-source pieces (Gmail, OpenAI, Slack, Notion, HubSpot)500+ pre-built nodes plus custom HTTP/GraphQL and cURL import
Code stepsTypeScript code step for the hardest stepsJavaScript and Python code steps anywhere in a workflow
AI agent toolingAI agents with custom instructions, human approval gates, Tables, MCP server for Claude/ChatGPT/Cursor/Copilot/GeminiMulti-agent and RAG pipelines, traceable AI reasoning, structured I/O enforcement, native AI evaluation, MCP support
Concurrency limitsNot stated in provided data5-concurrent executions on Starter, 20 on Pro
Target builderNon-engineers across sales, support, marketing, ops — no code neededIT Ops, SecOps, DevOps, and developers comfortable with Docker/self-hosting

Pick Activepieces if your buyers are non-engineers and you need AI agents with human approval gates running without anyone touching a terminal — the chat-to-workflow drafting and per-step approval gates are the differentiator. Pick n8n if your team is technical, writes JavaScript or Python, and needs to inspect every AI reasoning step with structured I/O and native evaluation before it hits production. The real split is who builds the flow: Activepieces assumes a marketer or ops lead; n8n assumes someone who can run Docker and read a debugger. If your non-technical staff must own the automations, n8n's friction and its €667/mo Business-tier entry for SSO/audit will bite you.

Activepieces
Activepieces

Open-source AI automation: chat-drafted flows, agents, tables, and 760+ app connections you can self-host.

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n8n
n8n

n8n is visual AI workflow automation with JavaScript and Python escape hatches, self-hostable and traceable end to end

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Pricing
Freemium
Freemium
Plans
$0/mo
$16/mo billed annually ($20/mo billed monthly)
$166/mo billed annually ($200/mo billed monthly)
Custom
From $36k/year
$0
20€/mo, billed annually
50€/mo, billed annually
667€/mo, billed annually
Custom
Popularity
3.8k views
5.8k views
Skill Level
Beginner-friendly
Intermediate
API Available
Platforms
WebAPI
WebAPI
Categories
🤖 Automation & Agents🕸️ Agent Frameworks & Orchestration
🤖 Automation & Agents🕸️ Agent Frameworks & Orchestration
Features
Chat to automation: describe a workflow in plain words and get a drafted flow
AI agents with custom instructions, tools, knowledge, and human approval gates
Drag-and-drop visual flow builder with branching, retries, waitpoints, and subflows
Error handling with runs that resume from their last checkpoint instead of restarting
760+ open-source app connections (pieces) including Gmail, Slack, HubSpot, OpenAI, Notion
Tables for storing data that both flows and agents can read and write
MCP server connecting agents to Claude, Copilot, Cursor, Gemini CLI, Windsurf, and Zed
HTTP piece for any REST or GraphQL API with authentication and pagination
TypeScript code step for logic the visual builder can't express
Human approval gates before steps that touch money, customers, or production
Bring your own AI keys: Anthropic, OpenAI, AWS Bedrock, Google Gemini
Projects for isolating each team's or client's workspace
SSO via Okta or Entra with standard and custom roles
Audit logs streamed to your SIEM in real time
Secret managers keeping credentials in your own vault (e.g. HashiCorp Vault)
Visual drag-and-drop canvas with inputs and outputs beside each step's settings
JavaScript and Python code steps anywhere in a workflow
500+ pre-built integration nodes plus custom HTTP and GraphQL requests
Import cURL commands to create API nodes
MCP support for legacy systems and MCP-speaking tools
Build and update n8n workflows from inside your own AI app via MCP
AI agent builder with multi-agent setups and RAG pipeline support
Swap cloud or offline models without rebuilding workflows
Traceable AI reasoning — inspect prompt, response, and next action per execution
Human-in-the-loop approvals and rule-based guardrails for AI actions
Structured input and output enforcement to control data flow to and from AI steps
Native AI evaluation against real data plus a prompt testing framework guide (Sept 2026)
Re-run single steps, replay or mock data, and debug via the logs view
Queue mode with multiple instances and external S3 storage
Self-hosting via Docker, on-prem, and air-gapped deployments
Integrations
Slack
Gmail
HubSpot
OpenAI
Notion
Snowflake
QuickBooks
Stripe
GitHub
Google Sheets
Salesforce
Jira
PostgreSQL
Microsoft Graph
Datadog
Asana
ServiceNow
Zoom
Anthropic

What real users say: Activepieces vs n8n

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Activepieces

62 mentions across 4 sources · 76% positive (averaged across 4 sources)

Hacker News, YouTube, Product Hunt, GitHub

What users praise

  • • True open-source license (MIT) allows free use in commercial apps
  • • Drag-and-drop builder is praised for being easy and intuitive
  • • Active and responsive team; feature requests implemented in a day
  • • Very competitive pricing compared to Zapier and n8n

What frustrates them

  • • Advanced features are gated behind paid tiers, limiting open-source claim
  • • Fewer integrations than rivals (700 vs n8n's 1000+)
  • • Community edition lacks some power features, pushing users to paid plans
  • • Some users find n8n's workflow capabilities more advanced for complex automation

Researched Aug 21, 2026

n8n

105 mentions across 7 sources · 56% positive — mixed (averaged across 7 sources)

Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, GitHub, Lemmy

What users praise

  • • Self-host with Docker or n8n Cloud—full control over your data.
  • • Execution-based pricing, not per-step, unlike Zapier.
  • • Visual canvas with JavaScript/Python code steps anywhere.
  • • 500+ integrations and MCP support for legacy systems.

What frustrates them

  • • Not actually open source—Commons Clause restricts commercial use.
  • • Steep learning curve for non-technical users.
  • • UI is clunky and unintuitive, especially for beginners.
  • • Scaling workflows from test to production is problematic.

Researched Aug 18, 2026

Feature-by-feature

The capability split is about who sits at the keyboard. Activepieces leads with no-code: a chat interface where you describe a workflow in plain words, the agent drafts the flow, and 760+ pieces (Gmail, OpenAI, Slack, Notion, HubSpot) are assembled by drag-and-drop with branching, retries, waitpoints, subflows, and error handling. Tables give flows and agents a shared data store, an MCP server connects agents to Claude, ChatGPT, Cursor, GitHub Copilot, and Gemini, and human approval gates let a person sign off on steps touching money, customers, or production — reinforced by the July 2026 push on vibe automation and safe-agent operation. n8n leads with technical control: JavaScript and Python code steps anywhere in the canvas, cURL-imported API nodes, per-step input/output inspection, and traceable AI reasoning so you can read the prompt, response, and next action of every AI step. Its AI stack goes deeper on rigor — multi-agent setups, RAG pipelines, structured input/output enforcement on AI steps, rule-based guardrails, and native AI evaluation against real data. Both support MCP, both support human-in-the-loop approvals, both self-host. The difference: Activepieces optimizes for a non-engineer shipping an agent today; n8n optimizes for an IT Ops or SecOps engineer who must audit and regression-test the agent before and after it ships.

Pricing compared

Both are freemium and open-source, so the headline number is not where the decision lives — governance and concurrency are. Activepieces gates enterprise controls: SSO (Okta/Entra), audit logs, SCIM, secret managers, and standard or custom roles are paid-tier features, and its stated 'not for' is teams on the free tier expecting enterprise governance. The vendor threads its July 2026 news with a cost argument — positioning unlimited automations against quota-trap competitors like ClickUp — but the data here doesn't give a step price or tier list, so budget for the governance tier. n8n is more explicit about the ceiling: SSO and audit logging start at the €667/mo Business tier, and concurrency is capped at 5 concurrent executions on Starter and 20 on Pro. That means high-volume production flows queue behind those limits, which is a real cost hidden behind 'freemium'. If you need SOC 2 or HIPAA artifacts out of the box, n8n's own data says you won't get them there. Bottom line: Activepieces' cost story is per-step economics versus Zapier/Make; n8n's cost story is self-host the open source, but pay €667/mo the moment compliance and SSO enter the room.

Who should pick which

  • Ops or marketing lead with no engineering support
    Pick: Activepieces

    The chat-to-automation interface drafts flows from plain-English descriptions and the visual builder needs no code, so a non-technical owner can ship and maintain workflows themselves.

  • SecOps engineer building threat-intelligence pipelines
    Pick: n8n

    Traceable AI reasoning, structured input/output enforcement, and rule-based guardrails let every enrichment step stay auditable, which is exactly the SOAR-style requirement n8n targets.

  • Team migrating off Zapier or Make to cut per-step costs
    Pick: Activepieces

    Activepieces explicitly positions unlimited automations against quota-based models, and 760+ pieces cover the common SaaS integrations a Zapier user already runs.

  • Developer building multi-agent or RAG systems with custom code
    Pick: n8n

    JavaScript and Python code steps anywhere, RAG pipeline support, multi-agent builder, and native AI evaluation cover the build-and-regression-test loop Activepieces' TypeScript step alone won't.

  • Org needing air-gapped or EU-resident self-hosted agents with approvals
    Pick: Activepieces

    Self-hosted, air-gapped, and EU data residency are named, plus human approval gates and audit logs are built in rather than bolted onto a higher tier — provided you pay for the governance tier.

Frequently Asked Questions

Activepieces vs n8n: which should you choose?

Pick Activepieces if your buyers are non-engineers and you need AI agents with human approval gates running without anyone touching a terminal — the chat-to-workflow drafting and per-step approval gates are the differentiator. Pick n8n if your team is technical, writes JavaScript or Python, and needs to inspect every AI reasoning step with structured I/O and native evaluation before it hits production. The real split is who builds the flow: Activepieces assumes a marketer or ops lead; n8n assumes someone who can run Docker and read a debugger. If your non-technical staff must own the automations, n8n's friction and its €667/mo Business-tier entry for SSO/audit will bite you.

Can a non-technical person really build an agent in either tool?

Activepieces is explicitly designed for every department with a no-code chat-to-automation path. n8n's own 'not for' list names non-technical users who want plug-and-play without a server to think about, so this is the clearest single-axis decision.

Which one is cheaper at scale?

The data doesn't publish Activepieces' per-step or tier prices, so a hard number comparison isn't supported. n8n's disclosed constraints are the €667/mo Business tier for SSO/audit and 5- or 20-concurrent-execution caps on Starter and Pro, which are the costs that surface as you scale.

Do both support connecting agents to Claude, ChatGPT, or Cursor?

Activepieces ships an MCP server for exactly those clients. n8n also lists MCP support, including building and updating n8n workflows from inside your own AI app, so the distinction is workflow-management-through-MCP rather than mere connectivity.

What happens to a workflow when every step runs but one fails?

n8n lets you re-run a single step instead of the entire workflow, which matters on long multi-step AI pipelines. Activepieces handles failure through branching, retries, error handling, and waitpoints in the visual builder rather than step-level replay.

Which has more integrations?

Activepieces lists 760+ open-source pieces; n8n lists 500+ pre-built nodes but adds cURL import and custom HTTP/GraphQL so you can build what's missing. If you need 10,000+ niche connectors, Activepieces' own 'not for' note says Zapier and Make are still larger.

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Last reviewed: September 23, 2026