All your benchmarks

If you’re building AI workflows that think, adapt, and collaborate—n8n connects your tools, CrewAI lets your agents lead. One is the Swiss Army knife for automation; the other, a precision instrument for autonomous intelligence. This benchmark isn’t about which is better—it’s about which is right for the work you’re doing.

Feature n8n CrewAI
Category Workflow Automation Platform AI Framework
Primary Use Case Multi-step automation with app integrations and code nodes Orchestrating autonomous AI agents in collaborative crews
Core Strength Low-code/no-code with deep app integration and self-hosting High-performance, standalone multi-agent orchestration with minimal dependencies
License Model Fair-code (Sustainable Use License); enterprise features require paid license MIT (fully open source)
Self-Hostable Yes (Docker, Kubernetes, on-premises, air-gapped) Yes (self-hosted or on-premise via Python environment)
Cloud Hosted Yes (managed n8n cloud) Yes (Crew Control Plane cloud trial available)
Deployment Flexibility Docker, npm, Kubernetes, cloud, on-prem, air-gapped Cloud, self-hosted, on-premise, Docker, Kubernetes, serverless-compatible
Programming Language JavaScript, Python (via code nodes) Python only
Integration Count 400+ pre-built app integrations 100+ tool integrations (LLMs, vector DBs, APIs)
AI Capabilities Native AI nodes, LangChain integration, prompt engineering, vector storage Standalone agent orchestration, RAG, memory, LLM-as-judge, observability
Agent Support AI agents via custom workflows and LLM nodes Native role-based autonomous agents with delegation and collaboration
Workflow Design Visual drag-and-drop editor with node-based logic Code-first via Python decorators and YAML configs
Trigger Types Webhooks, cron, manual, event-based Event-driven: Start, Listen, Router, Or, And
Flow Control Linear or branching via conditions in code nodes Native conditional branching, hierarchical, and sequential flows
Memory & State Session-based via workflow history; no built-in memory Short-term, long-term, entity memory; persistent state with JSON serialization
Vector Store Support Yes (via AI nodes and external tools) ChromaDB, Qdrant (native integration)
Observability Inline logs, error tracing, workflow history Langfuse, OpenTelemetry, Phoenix, metrics, tracing, tagging
Debugging Tools Re-run steps, replay/mock data, inline logs, error tracing Verbose mode, trace logs, Langfuse, Phoenix, deterministic validation
Customization Custom nodes via JS/Python, npm packages Custom tools, agents, tasks, and flows via Python and YAML
Human-in-the-Loop Manual triggers and approvals possible Explicitly supported via design
Security & Compliance RBAC, SAML, LDAP, audit logs, encrypted secrets, self-hosting for data control GDPR, HIPAA, SOC2 ready; data locality, secure integrations, access controls
Authentication SSO (SAML), LDAP, 2FA, OAuth2, Basic auth, API keys API key-based (via environment variables); enterprise auth via cloud
Version Control Git integration, workflow exports, versioning Git compatible; semantic versioning
Template Library 1,700+ pre-built templates Template marketplace launching Q2 2025; 100+ examples available
Pricing Model Pay per full workflow execution; free tier + enterprise plans Free open-source; enterprise subscription (contact sales)
Free Trial 14 days, no credit card required Crew Control Plane cloud trial
Learning Curve Steep for non-developers; intuitive for technical users Low for beginners, advanced for enterprise-scale use
Target Users Developers, non-technical users, IT, finance, marketing, startups, enterprises Developers, data scientists, enterprise engineers, AI practitioners
LLM Support Any via HTTP nodes or LangChain OpenAI, Gemini, Ollama, Llama 3.3, NVIDIA NIM, Anthropic, Hugging Face
Tool Customization Yes, via code nodes and custom integrations Yes, via Python tools with strict reliability requirements
Performance Optimized for automation, not high-throughput backends 5.76x faster than LangGraph in QA tasks; seconds to minutes per run
Scalability Not designed for high-load production backends Supports hundreds of agents and thousands of tasks
Documentation Quality Comprehensive, well-structured Excellent, with guided courses and examples
Community Support Active forum, GitHub, YouTube tutorials 100k+ certified developers; active Discord/community channels
Integration with Other Frameworks LangChain, Zapier, Make.com LangChain, Autogen, LangGraph, Vercel AI SDK
Best For Teams needing app integrations, self-hosting, and cost-effective automation AI teams building autonomous, production-grade agent workflows with minimal boilerplate
Not Recommended For High-throughput backends, users without programming knowledge, true open-source licensing needs Non-technical users without Python access; legacy systems without Python 3.10+

If you’re building complex workflows that connect dozens of apps—like CRM, email, databases, and APIs—and need to self-host securely without relying on cloud-only tools, n8n is your quiet workhorse.

If you’re a developer or AI engineer designing autonomous agents that reason, collaborate, and remember—without writing endless boilerplate—CrewAI gives you the precision and speed to ship production-grade AI teams in days, not weeks.

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