Productivity · Head-to-head

n8n vs Glean

n8n (freemium, AI Score 8.7/10) vs Glean (paid, AI Score 8.4/10). Side-by-side pricing, features, pros and cons, and which to pick.

The verdict

Pick n8n if…
  • you need a genuinely free option
  • budget is the constraint
  • your primary use case is developer-adjacent ops and engineering teams who want ai agents and internal integrations running on infrastructure they control, with server costs instead of a per-task meter.
  • you need: development
Try n8n →
Pick Glean if…
  • your primary use case is enterprise it and knowledge-management leads at 1,000+ seat companies whose work is split across both google and microsoft plus slack, jira and salesforce, and who need search that respects existing permissions.
  • you need: research, support
Try Glean →

Side-by-side specs

Spec n8n Glean
Category Productivity Productivity
Pricing model freemium paid
Headline pricing Free self-hosted + Cloud from ~$20/mo Custom enterprise pricing — check website for current rates
Free tier Community edition is free and self-hosted with unlimited workflows and executions; you pay only for the server. Cloud plans have a time-limited trial. Cloud tier prices and execution allowances change periodically — check n8n.io/pricing before quoting them.
AI Score 8.7/10 8.4/10
Best for Developer-adjacent ops and engineering teams who want AI agents and internal integrations running on infrastructure they control, with server costs instead of a per-task meter. Enterprise IT and knowledge-management leads at 1,000+ seat companies whose work is split across both Google and Microsoft plus Slack, Jira and Salesforce, and who need search that respects existing permissions.
Editor's pick
Use cases productivity agents development research productivity agents support
Date added 2025-08-01 2026-05-01

Pros and cons

n8n logo

n8n

Productivity · freemium

Pros

  • Self-hosted community edition runs unlimited workflows and executions for infrastructure cost only, with no per-task meter
  • Model-agnostic AI nodes span OpenAI, Anthropic, Google, Mistral, Groq and xAI plus local models via Ollama, so an agent can run with zero external API calls
  • MCP support works both ways — consume external MCP servers as agent tools, or expose a workflow as an MCP server to outside assistants
  • Code node runs JavaScript or Python inline, so a missing connector is solvable rather than blocking
  • Large public template library and an unusually active community, which shortens the path from idea to working workflow

Cons

  • ×Fair-code, not open source — the Sustainable Use License bars offering it as a service, and SSO, RBAC, environments and log streaming are gated behind the enterprise license
  • ×Running it seriously means queue mode with Redis and worker containers; the one-container Docker demo does not survive real agent load
  • ×Cloud plans meter by execution, and an agent that retries and branches burns through an allowance far faster than the old two-step automations those tiers were sized for
  • ×Steeper than Zapier or Make for non-developers — expression syntax and n8n's item-array data model are where most newcomers get stuck
Glean logo

Glean

Productivity · paid

Pros

  • Mirrors each source system's permissions per user, so answers can't surface documents the searcher lacks access to — the failure mode that sinks most in-house RAG projects
  • Genuinely broad connector library (100+) covering both the Google and Microsoft worlds, plus Slack, Atlassian, Salesforce and developer tooling
  • Model-agnostic: not locked to one lab's stack, with customer-hosted and BYO-model paths for regulated buyers
  • Agents can write back into source systems and speak MCP, so it functions as an action layer rather than only a question-answering surface

Cons

  • ×No self-serve tier and no published pricing — every deployment routes through sales and an IT-led rollout
  • ×Microsoft 365 Copilot and Google Gemini Enterprise now ship comparable grounded search bundled with suites most buyers already own, making Glean a second line item to justify
  • ×Answer quality tracks source-data hygiene: stale wikis and over-shared drives produce confidently wrong answers, and cleanup is on you
  • ×Value scales with how fragmented your stack is — a company living almost entirely inside one suite gets far less out of it
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Updated 2026-08-10. Spec data sourced from official product pages and tracked in our public directory at /tools.