Make.com vs n8n: The Mid-Market Comparison Framework for Operations Managers
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Updated: July 2026. All pricing verified against Make.com and n8n on July 7, 2026.
Quick Verdict: Make.com vs n8n for Mid-Market Operations Teams
| Make.com Pro | n8n Cloud Pro | n8n Self-Hosted | |
|---|---|---|---|
| Monthly (annual billing) | ~$21/mo | $50/mo | ~$7/mo (VPS) |
| Credits / Executions | 10,000 credits/mo | 10,000 executions/mo | Unlimited |
| Billing unit | Per module run | Per workflow run | None |
| Users | Unlimited | Unlimited | Unlimited |
| Self-hosting option | No | No (cloud plan) | Yes |
| AI agents included | Yes | Yes (150 credits) | Yes (native LangChain) |
| Integrations | 3,000+ (maintained) | 500+ native + community nodes | 500+ native + community nodes |
| Custom code (JS/Python) | Paid plans only | All plans | All plans |
| Data residency control | Make’s cloud only | n8n EU servers (Frankfurt) | Full control |
| SSO / SAML | Enterprise only | Business ($667/mo) or Enterprise | Business ($667/mo) or Enterprise |
| Pricing URL | make.com/en/pricing | n8n.io/pricing | n8n.io/pricing |
TSA Verdict: Make.com vs n8n for operations managers is a deployment decision before it is a features decision. Make.com wins for non-technical ops teams needing fast deployment across 3,000+ SaaS apps with zero infrastructure overhead. n8n wins for teams with a technical operator on staff, data residency requirements, or automation volume above 30,000 workflow runs per month where self-hosted n8n eliminates per-credit billing entirely. The cost gap at scale is not marginal — it is structural.
Make.com vs n8n resolves differently depending on which question you ask first. Ask “which is cheaper?” and the answer depends on your volume and whether your team can run a VPS. Ask “which is faster to deploy?” and Make.com wins by two weeks. Ask “which handles AI-native workflows better?” and n8n has pulled ahead decisively in 2025–2026. The right Make.com vs n8n answer for an operations manager is the one that accounts for all three.
Two platform changes in the last 12 months affect every Make.com vs n8n comparison published before mid-2025. Make renamed its billing unit from “operations” to “credits” in August 2025. Standard module runs cost the same, but AI and code execution modules now consume credits differently. n8n removed its permanent free cloud tier in late 2025; cloud hosting now starts at $24/month on the Starter plan. n8n also removed all active workflow limits across every cloud plan in April 2026. Previously, lower tiers capped the number of simultaneously active workflows. Both changes are still missing from most comparison articles indexed today.
Pricing: The Make.com vs n8n Cost Comparison That Actually Matters
The Billing Unit Difference
This is the most consequential difference in the Make.com vs n8n pricing model and the one most articles explain poorly.
Make.com charges per credit: one credit per module execution. Every step in a scenario that processes data burns one credit. A 5-module scenario running 2,000 times per month consumes 10,000 credits. Make.com Pro’s base allocation exactly. Run that same scenario at 2,001 triggers and you hit an overage at 25% above the plan rate for additional 10,000-credit packs (~$11 each).
n8n Cloud charges per execution: one execution per complete workflow run, regardless of how many nodes the workflow contains. A 5-node workflow and a 50-node workflow each consume one execution when triggered. A 50-step n8n workflow triggered 2,000 times per month uses 2,000 executions. The same work on Make.com costs 100,000 credits.
For simple 2–3 step scenarios, Make.com and n8n Cloud have similar effective cost per unit of work. For complex 10–20 node workflows, n8n’s per-execution model is 5–15x cheaper than Make.com’s per-credit model at equivalent trigger volume.
Cost at Three Mid-Market Volumes
Volume 1: 5,000 workflow runs per month, 6-step workflows
- Make.com: 5,000 × 6 = 30,000 credits. Exceeds Pro’s 10,000-credit base. Requires 2 additional 10,000-credit packs at ~$11 each. Total: ~$43/month.
- n8n Cloud Pro: 5,000 executions. Exactly half the Pro plan’s 10,000-execution limit. Cost: $50/month.
- n8n Self-Hosted: Unlimited executions. VPS cost: ~$7/month.
Make.com is cheaper than n8n Cloud Pro at this volume. That advantage exists only because n8n’s execution model has a higher floor cost at the Pro tier. Self-hosted n8n is cheaper than both by $36–43/month.
Volume 2: 15,000 workflow runs per month, 8-step workflows
- Make.com: 15,000 × 8 = 120,000 credits. Requires Pro base (10,000) + 11 additional credit packs at $11 each = ~$142/month.
- n8n Cloud Pro: 15,000 executions. 50% over the 10,000-execution cap. Requires either upgrade to Business ($667/month) or purchasing execution packs (~$10–20 per 2,500 additional). Total: $70–110/month estimated.
- n8n Self-Hosted: Unlimited executions. VPS cost: ~$7/month.
At this volume, n8n Cloud Pro with overage packs beats Make.com on cost. Self-hosted n8n is the only option that does not scale billing with volume.
Volume 3: 50,000+ workflow runs per month, 10+ step workflows
- Make.com: 50,000 × 10 = 500,000 credits. Enterprise pricing territory. Custom quote required.
- n8n Cloud: Business plan at $667/month for 40,000 executions. Above that, Enterprise custom.
- n8n Self-Hosted: ~$15–20/month for a 4GB VPS handling this volume. Unlimited executions.
At 50,000+ monthly workflow runs, self-hosted n8n is the only platform in this comparison with a fixed, predictable cost that does not increase with volume.
The Make.com polling trap:
Make.com charges credits for scheduled polling triggers even when no new data arrives. A Make.com scenario checking a Gmail inbox every minute burns 43,200 trigger credits per month before any action runs. On Pro’s 10,000-credit allocation, a single polling trigger exhausts the plan 4x over. The fix: use webhook triggers wherever the source app supports them. A webhook fires only when new data arrives, consuming one credit per actual event. Auditing active scenarios for polling triggers and converting them to webhooks is the highest-ROI Make.com cost optimization available.
Deployment Model: The Decision Point Most Ops Managers Miss
This is where Make.com vs n8n diverges most sharply for mid-market operations teams.
Make.com is cloud-only. No self-hosting option exists on any plan. Your workflow logic, credentials, and data pass through Make’s infrastructure. Make holds SOC 2 Type II certification and GDPR compliance. For most mid-market B2B service agencies, this is acceptable. For teams handling regulated data — healthcare, financial services, government procurement — cloud-only deployment may not clear internal security review.
n8n offers both deployment paths. n8n Cloud (Starter at $20/month, Pro at $50/month) is fully managed: no servers, no Docker, no infrastructure overhead. n8n Community Edition (self-hosted, free) provides unlimited executions and full source access on your own infrastructure. The self-hosted Business plan ($667/month, self-hosted) adds SSO, Git-based version control, and multi-environment staging — features that Make.com gates behind Enterprise custom pricing.
For an operations manager evaluating Make.com vs n8n at a 10–30 person agency: if no one on the team has ever run a Docker container, start with Make.com. The time cost of learning infrastructure management eats the per-credit savings within the first six months. If the team has a technical operator who handles internal tooling, self-hosted n8n on a $7/month Hetzner VPS is the rational choice above 10,000 monthly workflow executions.
TSA SCAR: n8n Cloud Hard Stop on Execution Limit
Verified failure pattern from n8n documentation and user reports, July 2026.
n8n Cloud stops all workflows immediately when the monthly execution cap is reached. No grace period, no overage billing, no warning-and-continue behavior. Workflows simply stop executing until the next billing cycle resets. The Starter plan’s 2,500-execution limit can be exhausted in under 9 days by a single polling workflow checking for new data every 5 minutes (8,640 executions per month). For operations teams where automation downtime has direct client-facing consequences (missed onboarding triggers, delayed invoice sends, stopped CRM updates): this hard-stop behavior is a business continuity risk. Make.com continues running scenarios past the credit limit and bills at 125% of the plan rate. n8n Cloud does not. Budget the Pro plan (10,000 executions) minimum for any production workflow, and use webhook triggers rather than polling schedules wherever possible to conserve executions.
Integration Breadth: Where Make.com Holds a Structural Advantage
Make.com ships 3,000+ company-maintained integrations. Every connector in Make’s library is built and maintained by Make’s engineering team, which means trigger types, dynamic field dropdowns, OAuth flows, and error handling are consistently polished across the catalog.
n8n ships 500+ native integrations plus a community node library. Community nodes are built by n8n’s open-source contributor base. They cover tools not in the native catalog but vary in maintenance quality and update frequency. For niche SaaS tools, industry-specific platforms, or regional software not in Make’s library, community nodes fill the gap. For mainstream SaaS stacks (HubSpot, Salesforce, Slack, Google Workspace, Notion, ClickUp, Stripe), both platforms cover identical ground.
The practical implication for mid-market operations teams: if your agency’s tech stack includes tools in Make’s 3,000-app library, Make.com’s integration advantage is real and measurable in deployment speed. If your stack is mainstream SaaS, the gap is minimal.
TSA SCAR: n8n Community Node Security Risk
Verified from n8n documentation and security advisories, July 2026.
n8n’s community node library allows third-party developers to publish nodes for tools not in the native catalog. These nodes are not reviewed or maintained by n8n’s core team. A community node can contain outdated dependencies, insecure credential handling, or no active maintainer. Operations teams using community nodes on self-hosted n8n instances for production workflows should audit each community node before deployment: check the node’s GitHub repository for last commit date, open issues, and whether the original developer is still active. Never install a community node with no commits in the past 12 months for a workflow handling client data. Make.com has no community node equivalent. Every integration is maintained by Make’s engineering team.
AI Automation: Where n8n Has Pulled Ahead of Make.com
This is the axis where the Make.com vs n8n comparison has shifted most significantly in 2025–2026.
Make.com AI agents are available on all paid plans via the Make AI Agent node and integrations with OpenAI, Anthropic, Google AI, and Azure AI. Make’s AI implementation is module-based: you add an AI step to a scenario the same way you add any other module. The result is accessible for non-technical ops teams — no code, drag-and-drop setup, pre-built templates. The limitation is architectural: AI logic in Make must be manually sequenced as separate modules. There is no native AI tool-routing, memory persistence across runs, or agent-to-agent orchestration framework.
n8n AI agents are built on native LangChain integration with purpose-built agent architecture: tool-use routing (the AI decides which action to take based on input data), memory nodes that persist context across workflow runs, RAG support via vector database connections (Pinecone, Qdrant, Supabase pgvector), and the ability to connect local LLMs via Ollama. For operations teams building AI-powered intake workflows, autonomous data enrichment pipelines, or multi-step AI decision systems, n8n’s agent architecture handles complexity that Make’s sequential module approach cannot replicate cleanly.
The community consensus in 2026: n8n has pulled ahead on AI-native capabilities. Make remains the faster way to ship an AI-enhanced workflow that a non-engineer can maintain. If the AI use case is “add a GPT summarization step to my CRM workflow,” use Make. If it is “build an autonomous agent that researches incoming leads, scores them, and routes them to different sequences based on LLM reasoning,” use n8n.
Feature Comparison: Mid-Market Operations Manager Use Cases
| Feature | Make.com Pro | n8n Cloud Pro | n8n Self-Hosted |
|---|---|---|---|
| Billing model | Per credit (per module run) | Per execution (per workflow run) | None |
| 10K complex runs/month cost | $21–43/mo (credit overages) | $50/mo | ~$7/mo |
| Self-hosting option | No | No | Yes |
| Data residency control | Make’s servers only | EU Frankfurt | Full |
| AI agent architecture | Sequential modules | Native LangChain + tool-routing | Native LangChain + tool-routing |
| Custom JavaScript/Python | Paid plans | All plans | All plans |
| Native integrations | 3,000+ (maintained) | 500+ native | 500+ native + community |
| Git version control | No | Business tier ($667/mo) | Business tier ($667/mo) |
| SSO / SAML | Enterprise (custom) | Business ($667/mo) | Business ($667/mo) |
| Multi-environment (dev/staging/prod) | No | Business tier | Business tier |
| Support model | Paid plans: email/chat | Cloud: email/community | Community forum / GitHub |
| Setup time (non-technical) | Hours | Hours (cloud) | Days (self-hosted) |
| Workflow hard stop at limit | No (bills overage) | Yes (stops immediately) | N/A (unlimited) |
Data Portability: Switching Costs From Make.com and n8n
Make.com: Scenarios export as JSON bundles via the Make API or manual download. The export format captures logic, module configuration, and connection structure. Importing Make.com scenarios into any other platform requires complete rebuild — the JSON is Make-proprietary. Credentials do not transfer. Expect 1–3 hours of rebuild per complex scenario on migration.
n8n: Workflows export and import as JSON natively. n8n’s JSON format is portable between n8n instances — migrating from n8n Cloud to self-hosted n8n is a JSON export and import, with only credential reconnection required. Migrating from n8n to Make.com or Zapier requires full rebuild. The self-hosted path creates the lowest lock-in of any platform in this comparison: your workflow logic runs on your infrastructure, exports cleanly, and re-imports without licensing dependency.
Buy / Skip Decision Matrix: Make.com vs n8n
| Scenario | Verdict |
|---|---|
| Non-technical ops team, no internal DevOps support | Make.com Pro |
| Needing 3,000+ integrations with polished maintained connectors | Make.com Pro |
| Under 10,000 workflow runs per month, simple 2–5 step scenarios | Make.com Core ($12/mo) |
| Need polished AI steps without code, non-technical team | Make.com Pro |
| Technical ops team comfortable with Docker and a VPS | n8n Self-Hosted |
| Data residency requirement — healthcare, finance, regulated data | n8n Self-Hosted (only viable option) |
| Over 10,000 complex (8+ step) workflow runs per month | n8n Self-Hosted |
| Building AI agents with tool-routing, memory, or RAG | n8n (cloud or self-hosted) |
| Need SSO without paying Enterprise pricing | n8n Business ($667/mo, self-hosted) |
| Git-based version control for workflow governance | n8n Business (self-hosted) |
| Automation hard stop at limit is unacceptable for ops continuity | Make.com (bills overage, keeps running) |
| Starting out — zero automation experience, no engineers | Make.com Free tier (1,000 credits) |
FAQ
Is Make.com or n8n cheaper for mid-market agencies in 2026?
It depends on workflow complexity and whether self-hosting is viable. Make.com Pro at $21/month is cheaper than n8n Cloud Pro at $50/month at low volumes. At volumes above 10,000 monthly workflow runs on complex 8+ step scenarios, Make.com’s per-credit model generates meaningful overage costs. Self-hosted n8n on a $7/month VPS eliminates per-execution billing entirely and is the cheapest option at any volume above 2,000 monthly workflow runs, assuming someone on the team can manage basic infrastructure.
What changed in Make.com pricing in August 2025?
Make.com renamed “operations” to “credits” in August 2025. For standard module runs, the cost is identical: one credit per module execution. The change unified the metering language across standard and AI features. AI-related modules and code execution now consume credits at variable rates. Most guides written before late 2025 still use “operations”; substitute “credits” when reading older documentation.
What changed in n8n pricing in 2025–2026?
Two significant changes. First, n8n removed its permanent free cloud tier in late 2025. Cloud hosting now starts at $24/month (Starter, 2,500 executions). Second, n8n removed all active workflow limits across every cloud plan in April 2026. Previously, lower-tier plans restricted the number of simultaneously active workflows. Now every plan, including Starter, allows unlimited active workflows, with execution count as the only usage constraint.
Can Make.com scenarios be migrated to n8n?
Not automatically. Make.com’s scenario JSON format is proprietary and does not import into n8n. Each workflow requires rebuild. The practical migration path: export Make.com scenario JSON as documentation, rebuild equivalent n8n workflows using the logic as reference, reconnect credentials. Budget 1–3 hours per complex workflow. n8n workflows export as JSON that re-imports cleanly between n8n instances, making future migrations within the n8n ecosystem frictionless.
Does n8n self-hosting require a dedicated DevOps engineer?
Not for basic deployment. A single non-technical operator following a Docker Compose guide can deploy n8n on a Hetzner or DigitalOcean VPS in under an hour. The ongoing maintenance requirement is light: apply n8n updates when notified, monitor disk usage, verify backups run. For teams already running any self-hosted tooling, n8n adds minimal overhead. For teams with no self-hosted infrastructure experience, the initial setup carries a realistic 2–4 hour learning curve, after which the system runs without daily attention.
Which platform is better for AI-powered automation workflows in 2026?
n8n for complex AI agent architectures. n8n’s native LangChain integration supports tool-routing, memory persistence, vector store connections, and local LLM support via Ollama. These are capabilities Make.com’s sequential module approach cannot replicate. Make.com for accessible AI steps in existing SaaS workflows: adding a GPT summarization step, running a classification module, or triggering an AI response on a form submission are faster to deploy on Make.com without code. For mid-market ops teams, the choice tracks directly with workflow complexity: if an ops manager can configure it, use Make.com. If it needs a developer, n8n delivers more capability per dollar.
