Which is actually cheapest at scale: n8n, Zapier, or Make?

n8n by a wide margin once you cross ~5,000 workflow runs/month, especially self-hosted. The structural reason is execution counting. n8n bills per workflow execution (one full run); Zapier bills per task (every step); Make bills per operation (similar to Zapier). A 10-step workflow that runs 1,000 times = 1,000 n8n executions but 10,000 Zapier tasks or Make operations. At Zapier's $0.025-0.05/task this is $250-500/mo on Zapier vs €24-60/mo on n8n cloud or ~$10/mo on n8n self-host. The cost gap compounds with workflow complexity.

What's the real difference between Zapier tasks, Make operations, and n8n executions?

It's the unit of billing and it's the most consequential pricing decision in the category. Zapier tasks = every step in a Zap counts. Make operations = every node action counts (similar but slightly different counting rules). n8n executions = one full workflow run is one execution regardless of step count. For workflows with 5+ steps, the n8n model is 5-10x more efficient. For 2-3 step workflows, the differences are smaller. The structural advantage of n8n grows linearly with workflow complexity.

Which has the most integrations?

Zapier dominates with 6,000+ native integrations — including thousands of niche SaaS tools the others don't natively support. Make has ~1,500 integrations. n8n has ~1,000 native nodes plus a generic HTTP node + custom code that connects to anything with an API. For mainstream B2B tools (Salesforce, HubSpot, Slack, Stripe, Shopify, Notion, GitHub, etc.) all three are fine. For niche industry-specific apps, Zapier's catalog is meaningfully larger; if your stack depends on an unusual SaaS tool, check each tool's catalog before committing.

Which is easiest for non-technical teams?

Zapier wins decisively for non-technical operators. The UX is built around plain-English Zap creation; the natural-language workflow builder (Zapier AI) makes the first 5-10 Zaps almost zero-friction. Make is in the middle — visual scenario builder is more powerful but requires comfort with bundles, iterators, and JSON paths. n8n assumes technical comfort with webhooks, JSON traversal, and execution branching; non-technical users take 2-4 weeks to get productive vs Zapier's 2-4 days.

Which is best for AI agent workflows in 2026?

n8n has built the most serious AI agent layer in the category. Native nodes for OpenAI, Anthropic, and Google Gemini; vector store integrations (Pinecone, Qdrant, Weaviate, Supabase); chain composition that supports tool-calling agents and multi-step reasoning. Make has solid AI scenarios with prompt engineering interfaces. Zapier launched AI Actions and natural-language workflow creation but is more 'AI-assisted automation' than 'agent framework'. For teams building real agent-style workflows (research, content pipelines, support triage), n8n is the strongest pick.

Can I self-host any of these?

Only n8n. The Community Edition is fair-code licensed, free, and runs unlimited executions on your own infrastructure ($5-20/mo VPS for SMB workloads). Zapier and Make are SaaS-only — no self-host option exists. For compliance-heavy industries (healthcare, financial services, government, ITAR), self-host is often the only viable option, which is why n8n wins those verticals by default. If self-host isn't a requirement, this point is moot.

Which is better for engineering teams?

n8n by clear margin. Code-extensible JavaScript nodes let engineering teams write inline custom logic, parse complex payloads, and implement business rules without leaving the workflow. Webhook handling, conditional branching, error handling, retry policies, and queue-mode execution are all first-class. The platform feels like a lightweight orchestration runtime, not a no-code toy. Zapier and Make have code steps too but they're add-ons rather than first-class. For engineers, the n8n philosophy fits how they already think about pipelines.

Which one should I pick for a brand-new project?

Pick by team profile, not feature list. (1) Non-technical team, <5k tasks/mo, mainstream integrations only → Zapier. (2) SMB with some technical comfort, want SaaS polish, OK with per-operation pricing → Make. (3) Engineering team, scaling above 5k workflow runs/mo, polling-heavy or AI-agent workflows, compliance requirements, or any plan to run automation as code → n8n. The pricing model alone usually decides it: if you're growing past Zapier's tier-3 limits, switch before you renew.

How hard is it to migrate from Zapier or Make to n8n?

Manual but straightforward. Workflows don't auto-import; each one is rebuilt in n8n's editor. A 30-workflow Zapier-to-n8n migration runs 60-120 hours of focused work spread over 2-6 weeks, including a parallel-run period for risk management. The bottleneck is integration coverage — workflows that depend on niche Zapier-only integrations need to be rebuilt with n8n's HTTP node + API docs. Cost savings usually pay back the migration in the first quarter; often the first month at scale.

What's the catch with n8n that buyers don't see?

Three things. (1) Documentation is uneven — newer features (especially AI agent nodes) lag the actual implementation; expect to read forum threads. (2) Error messages are sometimes vague — "Problem executing workflow" requires manual canvas inspection. (3) Polling triggers eat cloud execution budgets fast — a 5-min polling trigger burns 8,640 executions/month and exhausts the Starter plan in 9 days. None of these are dealbreakers, but they're the friction points new users hit.

StackSwap comparison · published 2026-05-06

n8n vs Zapier vs Make (2026): Operator Comparison + Decision Tree

Q: How hard is it to migrate from Zapier or Make to n8n?

Manual but straightforward. Workflows don't auto-import; each one is rebuilt in n8n's editor. A 30-workflow Zapier-to-n8n migration runs 60-120 hours of focused work spread over 2-6 weeks, including a parallel-run period for risk management. The bottleneck is integration coverage — workflows that depend on niche Zapier-only integrations need to be rebuilt with n8n's HTTP node + API docs. Cost savings usually pay back the migration in the first quarter; often the first month at scale.

Q: What's the catch with n8n that buyers don't see?

Three things. (1) Documentation is uneven — newer features (especially AI agent nodes) lag the actual implementation; expect to read forum threads. (2) Error messages are sometimes vague — "Problem executing workflow" requires manual canvas inspection. (3) Polling triggers eat cloud execution budgets fast — a 5-min polling trigger burns 8,640 executions/month and exhausts the Starter plan in 9 days. None of these are dealbreakers, but they're the friction points new users hit.

The honest three-way comparison most automation buyers actually need. Zapier wins on UX and integration catalog. Make is the polished SaaS middle ground. n8n is 5-15x cheaper at scale (especially self-hosted) and the strongest pick for engineering teams and AI agent workflows. Here's the decision tree by team profile, the real pricing math by volume tier, and the migration costs nobody talks about.

The 30-second answer

Zapier if your team is non-technical, you're running <5,000 simple workflow runs/month, and you depend on niche integrations from its 6,000+ catalog. The convenience is worth the per-task pricing tax at low volume.

Make if you're an SMB with some technical comfort, want SaaS polish, and run mid-volume workflows under ~50,000 operations/month. The middle ground answer.

n8n if you're an engineering team, scaling past Zapier's per-task wall, building AI agent workflows, polling-heavy, need self-host for compliance, or planning to run automation as code. 5-15x cost reduction at scale, code-extensible nodes, native AI agent layer.

The pricing model is the most important difference

Forget feature lists for a moment. The single most consequential decision in this category is the billing unit:

Zapier = per task. Every step in a Zap counts. A 10-step Zap that runs 1,000 times = 10,000 tasks.
Make = per operation. Every node action counts (similar counting rules to Zapier). Same scenario above ≈ 10,000 operations.
n8n = per execution. One full workflow run is one execution regardless of step count. Same workflow above = 1,000 executions.

For workflows with 5+ steps, n8n's pricing model is structurally 5-10x more efficient than Zapier or Make. The advantage compounds with workflow complexity. For simple 2-3 step workflows the differences are smaller and Zapier's ease-of-use advantage often wins.

Pricing math by volume tier

How the math actually plays out at the volume tiers we see most often. Costs are approximate — confirm current pricing on each vendor's site.

Volume tier	Zapier	Make	n8n cloud	n8n self-host	Winner
500 workflow runs/mo, 3 steps each (1.5k tasks/ops/execs)	~$30/mo (Starter)	~$10/mo (Core)	€24/mo (Starter)	~$5/mo (small VPS)	Make / n8n self-host
2,000 workflow runs/mo, 5 steps each (10k tasks/ops/execs)	~$50-100/mo (Pro)	~$30/mo (Pro)	€24/mo (Starter)	~$5/mo	n8n self-host (Make second)
10,000 workflow runs/mo, 8 steps each (80k tasks/ops/execs)	~$300-600/mo (Team)	~$200-400/mo (Pro+)	€60/mo (Pro)	~$10-20/mo	n8n (5-10x cheaper)
50,000 workflow runs/mo, 10 steps each (500k tasks/ops/execs)	~$1,500-3,000/mo (enterprise)	~$800-1,500/mo (Enterprise)	€800/mo (Business) or custom	~$50-100/mo	n8n (5-15x cheaper)
500,000+ workflow runs/mo (high-volume operations)	$5,000-15,000/mo enterprise	$3,000-8,000/mo enterprise	Custom enterprise	~$150-300/mo	n8n self-host (10-30x cheaper)

Side-by-side feature matrix

Feature	Zapier	Make	n8n	Winner
Pricing model	Per task (every step counts)	Per operation (similar to per task)	Per execution (one workflow = one count)	n8n
Self-host option	❌ No	❌ No	✅ Free Community Edition	n8n
Native integrations count	~6,000+	~1,500	~1,000	Zapier
Visual editor polish	⭐⭐⭐⭐⭐ Excellent	⭐⭐⭐⭐ Strong	⭐⭐⭐ Good	Zapier
Code-extensibility	⭐⭐ Code steps available	⭐⭐⭐ Code module	⭐⭐⭐⭐⭐ Native JS nodes	n8n
AI agent capabilities (2026)	⭐⭐⭐ AI Actions, NL workflow creation	⭐⭐⭐ AI scenarios, prompt UI	⭐⭐⭐⭐⭐ Native agent nodes + vector stores	n8n
Onboarding speed (non-technical user)	✅ Hours to first Zap	⚠️ Days to first scenario	⚠️ Weeks to productive	Zapier
Onboarding speed (engineering team)	⚠️ Constraints frustrate engineers	✅ Days to productive	✅ Days to productive	Make / n8n tied
Compliance / data sovereignty	SaaS-only, SOC2 Type 2	SaaS-only, GDPR-focused	Self-host = full sovereignty	n8n
Enterprise procurement (custom DPA, SLAs)	✅ Mature	✅ Mature	⚠️ Maturing (Series B funded)	Zapier / Make tied
Operator community	✅ Largest, most resources	✅ Strong, active	✅ Active GitHub + Discord (45k stars)	Zapier (size)
Vendor stability	Public-bound, mature	Acquired by Celonis 2020	Series B 2024 ($55M)	Zapier (most stable)

Decision tree by team profile

If you are...	Pick	Why
Non-technical marketing or ops team, <5k tasks/mo, mainstream integrations	Zapier	Best UX in the category. The 'pay the convenience tax' answer is right here — your team's productivity matters more than per-task pricing efficiency at this scale.
SMB with some technical comfort, want SaaS polish, mid-volume	Make	The middle ground. More powerful than Zapier, more polished than n8n, per-operation pricing is OK if you stay under 50k operations/mo.
Engineering-led ops or RevOps team	n8n	Code-extensible nodes + per-execution pricing fit how engineering teams already think about pipelines. Self-host or cloud, both fit the engineering workflow.
Hitting Zapier per-task pricing wall (>$300/mo)	n8n	5-10x cost reduction at equivalent volume. Migration pays back within the first quarter.
Compliance-heavy industry (healthcare, financial services, government)	n8n self-host	Self-host is often the only viable option for data sovereignty. Zapier and Make are SaaS-only.
Building AI agent workflows (research, content, support triage)	n8n	Native agent nodes + vector store integrations + chain composition is the most serious agent layer in the category.
Polling-heavy automations (price monitors, social listening, etc.)	n8n self-host	No execution cap on self-host means polling is free. Zapier or Make polling burns through monthly limits fast.
Team depends on niche industry-specific integrations Zapier supports natively	Zapier	Catalog size matters when your stack includes long-tail SaaS tools n8n and Make don't natively support. Pay the per-task tax for the catalog.
Embedded customer-facing automation (offering integrations to your SaaS users)	Tray.io or Workato	Different category. None of these three are built primarily for embedded automation. n8n is closing this gap but Tray and Workato have the embedded SaaS motion solved.
Fortune 500 IT-led integration project, deep governance requirements	Workato	Enterprise iPaaS with the procurement machinery, compliance certifications, and integration depth Fortune 500 IT expects. n8n is a fraction of the cost but a different sales motion.

Where Zapier wins

Integration catalog (6,000+ apps). By a wide margin. If your stack includes a niche industry SaaS tool, Zapier is the only one likely to support it natively.
UX for non-technical users. Plain- English Zap creation, AI-assisted natural-language workflow builder, the most forgiving learning curve in the category. Hours to first Zap vs days/weeks for the others.
Vendor maturity. Largest community, most templates, most operator resources. The default choice for a reason.
Enterprise procurement defaults. Mature enterprise sales motion, custom DPAs, multi-year contracts, certifications — all in place.
Tables + Interfaces bundle. If you need a low-code DB and UI alongside automation, Zapier's expanded product surface covers more of the bundle. n8n and Make stay focused on automation.

See zapier.com for current pricing.

Where Make wins

The polished SaaS middle ground. More powerful than Zapier's simpler abstraction, more polished than n8n's technical-leaning UX. The best feel-of-the-product among the three.
Integration depth (where they exist). Make integrations often expose more actions per app than Zapier's — fewer apps total but deeper coverage of the ones they have.
Visual scenario builder for complex flows. Bundles, iterators, aggregators, and conditional routers are well-modeled. For moderately complex workflows, Make is more intuitive than Zapier's linear Zap model.
European-native compliance posture. GDPR-focused from day one, EU data residency available. Useful for European teams with regional compliance requirements (though n8n self-host is the strongest answer for full sovereignty).
Mid-tier pricing. Often cheaper than Zapier per equivalent volume at SMB tiers. Not as cheap as n8n at scale.

See make.com for current pricing.

Where n8n wins

Pricing at scale. 5-15x cheaper than Zapier or Make above 5,000 workflow runs/month. Self-host eliminates the cost ceiling entirely for teams with DevOps capacity.
Self-host option. Free Community Edition, fair-code licensed, runs on your infrastructure. The only one of the three that supports this. Critical for compliance-heavy industries.
Code-extensibility. Native JavaScript nodes for inline custom logic. Engineering teams treat n8n as a lightweight orchestration runtime; the others as no-code tools with code escape hatches.
AI agent layer. The most serious agent implementation in the category — native nodes for OpenAI / Anthropic / Gemini, vector store integrations, chain composition supporting tool-calling agents.
No execution cap on self-host. Run polling triggers, high-frequency monitors, batch workloads — all free on infra you already pay for.
Community + GitHub culture. 45k+ stars, active Discord, community-built nodes for niche integrations. Open-source culture is part of the value prop.

Migration costs and payback

None of these tools auto-import workflows from each other. Migration is manual rebuild in the destination tool's editor. Here's what realistic migration looks like:

Migration	Realistic effort	Payback period
Zapier → n8n cloud	60-120 hours for 30 workflows (parallel-run + cutover)	1-3 months at >$300/mo Zapier spend
Zapier → n8n self-host	+ 1-3 hours setup, ongoing 30 min/quarter maintenance	< 1 month at >$500/mo Zapier spend
Make → n8n cloud	40-80 hours for 30 scenarios (Make and n8n share visual paradigms; rebuild is faster)	1-3 months at >$200/mo Make spend
Zapier → Make	50-100 hours for 30 workflows	Variable — Make is cheaper but not 10x cheaper at most volumes
n8n cloud → n8n self-host	~ 4-8 hours (workflows export and import directly)	< 1 month above 10-15k executions/mo

The payback math: if your Zapier or Make spend is >$300/mo, n8n usually pays back the migration within 1-3 months. Above $1,000/mo it's often less than a month. Run the calculation honestly — most teams either overestimate the migration time or underestimate the ongoing savings.

Common mistakes buyers make in this category

Picking by integration list before checking counting model. Two tools that both support Stripe and HubSpot can have a 10x cost difference based on how they bill. Check the counting model before the integration list.
Underestimating polling-trigger cost. A single 5-minute polling trigger = 8,640 executions/operations/tasks per month. Multiple polls compound fast. Use webhooks where possible; switch polling-heavy workflows to n8n self-host.
Buying enterprise tier on Zapier when n8n cloud would do the same job for 1/10 the price. At 50k+ runs/mo, Zapier's enterprise tier is $1,500-3,000/mo. n8n cloud Business is €800/mo for the same volume — and offers self-host upgrade if you cross the threshold.
Self-hosting n8n as a first DevOps project. The "free" tier costs more in time than cloud costs in money if your team has zero DevOps capacity. Start on cloud; migrate to self-host once volume justifies it.
Running two automation tools in parallel indefinitely. Common pattern: started on Zapier, hit limits, added Make for complex flows, kept both. Two contracts, fragmented governance, ops time spent reconciling. Consolidate on whichever tool covers >70% of your workflows; migrate the rest.

FAQ

Which is actually cheapest at scale: n8n, Zapier, or Make?: n8n by a wide margin once you cross ~5,000 workflow runs/month, especially self-hosted. The structural reason is execution counting. n8n bills per workflow execution (one full run); Zapier bills per task (every step); Make bills per operation (similar to Zapier). A 10-step workflow that runs 1,000 times = 1,000 n8n executions but 10,000 Zapier tasks or Make operations. At Zapier's $0.025-0.05/task this is $250-500/mo on Zapier vs €24-60/mo on n8n cloud or ~$10/mo on n8n self-host. The cost gap compounds with workflow complexity.
What's the real difference between Zapier tasks, Make operations, and n8n executions?: It's the unit of billing and it's the most consequential pricing decision in the category. Zapier tasks = every step in a Zap counts. Make operations = every node action counts (similar but slightly different counting rules). n8n executions = one full workflow run is one execution regardless of step count. For workflows with 5+ steps, the n8n model is 5-10x more efficient. For 2-3 step workflows, the differences are smaller. The structural advantage of n8n grows linearly with workflow complexity.
Which has the most integrations?: Zapier dominates with 6,000+ native integrations — including thousands of niche SaaS tools the others don't natively support. Make has ~1,500 integrations. n8n has ~1,000 native nodes plus a generic HTTP node + custom code that connects to anything with an API. For mainstream B2B tools (Salesforce, HubSpot, Slack, Stripe, Shopify, Notion, GitHub, etc.) all three are fine. For niche industry-specific apps, Zapier's catalog is meaningfully larger; if your stack depends on an unusual SaaS tool, check each tool's catalog before committing.
Which is easiest for non-technical teams?: Zapier wins decisively for non-technical operators. The UX is built around plain-English Zap creation; the natural-language workflow builder (Zapier AI) makes the first 5-10 Zaps almost zero-friction. Make is in the middle — visual scenario builder is more powerful but requires comfort with bundles, iterators, and JSON paths. n8n assumes technical comfort with webhooks, JSON traversal, and execution branching; non-technical users take 2-4 weeks to get productive vs Zapier's 2-4 days.
Which is best for AI agent workflows in 2026?: n8n has built the most serious AI agent layer in the category. Native nodes for OpenAI, Anthropic, and Google Gemini; vector store integrations (Pinecone, Qdrant, Weaviate, Supabase); chain composition that supports tool-calling agents and multi-step reasoning. Make has solid AI scenarios with prompt engineering interfaces. Zapier launched AI Actions and natural-language workflow creation but is more 'AI-assisted automation' than 'agent framework'. For teams building real agent-style workflows (research, content pipelines, support triage), n8n is the strongest pick.
Can I self-host any of these?: Only n8n. The Community Edition is fair-code licensed, free, and runs unlimited executions on your own infrastructure ($5-20/mo VPS for SMB workloads). Zapier and Make are SaaS-only — no self-host option exists. For compliance-heavy industries (healthcare, financial services, government, ITAR), self-host is often the only viable option, which is why n8n wins those verticals by default. If self-host isn't a requirement, this point is moot.
Which is better for engineering teams?: n8n by clear margin. Code-extensible JavaScript nodes let engineering teams write inline custom logic, parse complex payloads, and implement business rules without leaving the workflow. Webhook handling, conditional branching, error handling, retry policies, and queue-mode execution are all first-class. The platform feels like a lightweight orchestration runtime, not a no-code toy. Zapier and Make have code steps too but they're add-ons rather than first-class. For engineers, the n8n philosophy fits how they already think about pipelines.
Which one should I pick for a brand-new project?: Pick by team profile, not feature list. (1) Non-technical team, <5k tasks/mo, mainstream integrations only → Zapier. (2) SMB with some technical comfort, want SaaS polish, OK with per-operation pricing → Make. (3) Engineering team, scaling above 5k workflow runs/mo, polling-heavy or AI-agent workflows, compliance requirements, or any plan to run automation as code → n8n. The pricing model alone usually decides it: if you're growing past Zapier's tier-3 limits, switch before you renew.
How hard is it to migrate from Zapier or Make to n8n?: Manual but straightforward. Workflows don't auto-import; each one is rebuilt in n8n's editor. A 30-workflow Zapier-to-n8n migration runs 60-120 hours of focused work spread over 2-6 weeks, including a parallel-run period for risk management. The bottleneck is integration coverage — workflows that depend on niche Zapier-only integrations need to be rebuilt with n8n's HTTP node + API docs. Cost savings usually pay back the migration in the first quarter; often the first month at scale.
What's the catch with n8n that buyers don't see?: Three things. (1) Documentation is uneven — newer features (especially AI agent nodes) lag the actual implementation; expect to read forum threads. (2) Error messages are sometimes vague — "Problem executing workflow" requires manual canvas inspection. (3) Polling triggers eat cloud execution budgets fast — a 5-min polling trigger burns 8,640 executions/month and exhausts the Starter plan in 9 days. None of these are dealbreakers, but they're the friction points new users hit.