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n8n

Open SourceAutomation Last updated: April 13, 2026

n8n is a fair-code workflow automation platform with 400+ integrations, LangChain AI agents, JavaScript/Python code nodes, and free self-hosting for technical teams.

Pricing

Open Source

Free (self-hosted Community Edition); Cloud from €24/month

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Platforms

WebDesktopAPI

Capabilities

Context WindowN/A
API PricingN/A
Image Generation✗ No
Memory Persistence◑ Partial
Computer Use✗ No
API Available✓ Yes
Multimodal◑ Partial
Open Source◑ Partial
Browser Extension✗ No

Our Score

8.5/10
Functionality9.5
Features9.2
Usability7.0
Value9.5
Integrations7.5
Reliability8.0

Overview

n8n is a fair-code licensed workflow automation platform giving technical teams the flexibility of code with the speed of a visual node editor. Its Community Edition is free to self-host with no execution limits, all 400+ integrations, and full AI node access including 70+ LangChain-powered nodes for building agents with tool use, memory, and vector database integration. Cloud plans start at €24/month. Execution-based billing counts an entire workflow run as one execution regardless of step count — making n8n 10–20x cheaper than Zapier for complex multi-step workflows at equivalent volume. Self-hosting requires Docker, PostgreSQL, and basic DevOps capacity; realistic production infrastructure costs €20–150/month. The fair-code license restricts commercial SaaS use without a paid license.

Pricing

Plans & Pricing

Key Features

  • LangChain-powered AI Agent nodes with tool use, persistent memory, and vector database integration for building autonomous agents
  • Code node supporting JavaScript and Python with npm package installation on self-hosted instances for custom logic beyond visual nodes
  • Execution-based billing counting one complete workflow run as one execution regardless of step count or data volume processed
  • Community Edition free self-hosting with unlimited executions on Docker, Kubernetes, or air-gapped private networks
  • Human-in-the-Loop approval node requiring human sign-off before AI agents execute specified actions
  • MCP Client Node connecting n8n workflows to external Model Context Protocol servers as an action target

Pros & Cons

Pros

  • Community Edition self-hosting eliminates all n8n licensing fees — complex 50-step workflows cost server infrastructure only, delivering 10–50x cost savings versus Zapier at equivalent automation volume for teams with DevOps capacity
  • LangChain-powered AI Agent architecture with 70+ AI nodes is the most technically capable AI workflow layer among no-code/low-code automation platforms — supporting multi-agent orchestration, RAG pipelines, and vector database integration natively
  • Code node with JavaScript, Python, and npm packages on self-hosted instances gives developers full programmatic control within the visual workflow without exiting to an external service
  • Air-gapped self-hosted deployment with custom data residency satisfies HIPAA, GDPR, and SOC 2 data sovereignty requirements that cloud-only competitors cannot meet

Cons

  • Community Edition requires Docker/server setup with DevOps capacity — realistic production deployments cost €20–150/month in infrastructure and ongoing engineering time for updates, SSL, and monitoring; teams without server management experience should use Cloud
  • Cloud Starter's 2,500 executions/month are exhausted in 9 days by a single polling trigger checking every 5 minutes — high-frequency or multi-workflow teams will rapidly require the 10x more expensive Pro plan or Business plan
  • Fair-code license restricts commercial SaaS use — teams building products that include n8n as a service component require an Enterprise license; the Community Edition is for internal use only
  • Steeper learning curve than Zapier and Make — concepts like sub-nodes, cluster nodes, queue mode, and LangChain agent architecture require significant technical investment before confident production deployment

Who It's For

Best For

  • Developers and technical teams who need the deepest AI agent architecture with LangChain, vector databases, and custom code within a visual automation platform
  • Organisations in regulated industries requiring air-gapped self-hosted deployment, custom data residency, and full control over where automation infrastructure runs
  • Startups and high-volume automation teams where self-hosted Community Edition eliminates per-execution costs that would otherwise make Zapier or Make prohibitively expensive at scale
  • Teams building complex multi-step workflows where execution-based billing delivers 10–20x cost savings versus per-task platforms at equivalent automation volume

Not Ideal For

  • Non-technical teams or individuals who need to build automations without any server management, Docker knowledge, or DevOps capacity — Zapier or Make's cloud-only offerings remove all infrastructure overhead
  • Teams whose SaaS stack relies heavily on the ~6,600 apps in Zapier's integration library that n8n does not natively support — n8n's HTTP Request node covers most APIs but requires manual configuration
  • Teams building a commercial SaaS product that includes n8n functionality — the fair-code license requires an Enterprise license for commercial SaaS use, significantly raising total cost
  • Low-volume automation users generating fewer than 2,500 executions/month who do not need self-hosting — Zapier Professional at $19.99/month or Make Core at ~$9/month are simpler and cheaper for minimal automation workloads

Use Cases

Automation

9.5/10

Execution-based billing counts a 50-step workflow as 1 execution versus 50 tasks on Zapier, making n8n 10–20x cheaper for complex automations at equivalent volume; Code node adds JavaScript and Python for custom logic unavailable in Zapier or Make; air-gapped self-hosted deployment supports compliance-sensitive production environments.

Coding

9/10

Code node supports JavaScript and Python with npm package installation on self-hosted instances; HTTP Request node connects to any REST API without a pre-built integration; Git-based source control enables environment promotion workflows; LangChain node architecture supports building custom AI agent tools in code.

Data Analysis

8.2/10

Iterators, aggregators, and Code node enable batch data processing, transformation, and enrichment pipelines; native PostgreSQL, MySQL, and MongoDB nodes support direct database reads and writes; vector store integrations (Pinecone, Qdrant, Weaviate) support RAG pipelines for AI-augmented data analysis workflows.

Marketing

7.8/10

400+ integrations cover CRM, email, social, and analytics tools; execution-based pricing makes high-frequency campaign automation affordable; steeper learning curve than Zapier or Make reduces accessibility for non-technical marketing team members who need to build and maintain their own automations.

Research

8.5/10

LangChain AI agents with tool use and persistent memory support autonomous research workflows; MCP Client Node connects to external AI agent action registries; Human-in-the-Loop approvals shipped January 2026 enable supervised AI research pipelines; self-hosting ensures research data stays on controlled infrastructure.

Consider These Instead

When Not To Choose n8n

Choose Zapier when the automation stack includes niche or industry-specific apps absent from n8n's ~400 integrations, when non-technical team members need to build and maintain workflows without any DevOps involvement, or when Copilot and mature AI Agents with the largest pre-built integration library are the priority. Choose Make when the required integrations are within Make's ~3,000-app library and a visual canvas with Routers, Iterators, and Aggregators covers the workflow complexity needed — Make provides a middle ground of visual power at lower cost than Zapier without the DevOps requirement of n8n self-hosting. Choose Microsoft Power Automate when the organisation is fully Microsoft 365-native and automation within Teams, SharePoint, and Office applications is the primary use case included in existing licensing.

Integrations

OpenaiAnthropic (Claude)Google WorkspaceSlackPostgresqlHttp Request (Any Rest Api)WebhooksGithub

Known Limitations

learning curveecosystem weaknesspricing complexityreliability risk

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