Side-by-side

WSO2 Agent Manager vs n8n

WSO2 Agent Managern8n

Bottom line: WSO2 Agent Manager for enterprises managing many AI agents across teams; n8n for developers and technical teams who want code flexibility inside a visual builder.

	WSO2 Agent Manager Open-source control plane to deploy, observe, and govern AI agents Visit	n8n n8n is an open-source workflow automation platform that lets users build complex automations through a visual, node-based interface Visit
Votes	0	0
Pricing	Freemium	Freemium
Category	Automation	Automation
Tags	ai agent governancecontrol planeopen sourceguardrailsagent identitymcp	automate-workflowswrite-code
Best for	Enterprises managing many AI agents across teams Organizations that require data sovereignty and self-hosting Platform and security teams standardizing agent governance	Developers and technical teams who want code flexibility inside a visual builder DevOps and IT operations teams automating internal processes Security operations teams handling incident enrichment and response
Pros	Open source under the Apache 2.0 license Self-host for full data sovereignty or use managed SaaS More than 40 built-in guardrails mapped to the OWASP Top 10 Verifiable agent identity with instant revocation Broad framework support via OpenTelemetry, OpenAPI, and MCP	The hybrid no-code/code model is genuinely flexible: you can build the majority of a workflow visually and then drop into JavaScript or Python for the parts that need custom logic, avoiding the dead ends common to pure no-code tools. Self-hosting under a fair-code license gives teams full control over data residency and infrastructure, which matters for security operations, compliance-sensitive workloads, and organizations that don't want sensitive data routed through a third-party cloud. Execution-based pricing that charges per completed workflow run, rather than per step or per user, can dramatically lower costs for complex multi-step automations and removes the seat-counting friction of per-user platforms. Strong AI and agent tooling is built in, with nodes for LLM connections RAG pipelines, and agents whose reasoning steps stay visible and traceable on the canvas instead of being hidden in a black box.
Cons	Self-hosting an enterprise control plane requires significant operational effort Kubernetes expertise expected for the sandboxed runtime Public pricing for the managed SaaS tier is not published Aimed at enterprises rather than individual developers Recently reached general availability, so some capabilities are new	The platform has a meaningful learning curve; its power and code-friendly design assume technical comfort, making it less approachable for non-technical business users than simpler no-code automation tools. Self-hosting trades licensing savings for operational overhead — you take on hosting, scaling, monitoring, and maintenance, and AI agent token costs accrue on top regardless of deployment. Execution-based pricing is cost-efficient but can be hard to predict, since high-volume or frequently triggered workflows can consume execution allowances faster than expected. Some advanced governance and collaboration features (such as SSO/SAML Git-based version control, and different environments) are gated to higher Business and Enterprise tiers.

Comparison generated from each tool's listing. Add or remove tools above to change it.