Founder of Erudience. Head of AI at Absolute Intelligence UK. Ships production n8n and voice AI systems for UK and international teams.
n8n is best for engineer-owned, git-versioned, self-hostable automation with the lowest cost at scale. Make is best for visually complex workflows with strong error routing without touching infrastructure. Zapier is best for the widest integration catalogue and the fastest first-Zap experience, at the highest cost per task once volume grows.
Short answer for 2026: pick n8n if you want ownership, git versioned workflows, and predictable cost at scale. Pick Make if you want a strong visual builder with rich integrations and no interest in self hosting. Pick Zapier when speed to the first working automation matters more than long term cost or control.
The rest of this piece is the honest version of that answer, based on running production automation systems on all three across UK and international clients.
n8n vs Zapier vs Make, side by side
Snapshot of the trade-offs that matter for production workflows in 2026.
| Criterion | n8n | Make | Zapier |
|---|---|---|---|
| Hosting model | Self-host or n8n Cloud | Cloud only | Cloud only |
| Pricing model | Per instance (self-host) or per active workflow (Cloud) | Per operation | Per task |
| Free tier | Community edition (self-host, unlimited) | 1,000 ops / month | 100 tasks / month |
| Starter paid plan | ~$24/mo (Cloud Starter) | ~$9/mo (10k ops) | ~$29.99/mo (750 tasks) |
| Cost at 50k executions/mo | ~$20–$60 infra (self-host) | ~$200–$400 | ~$700–$1,000 |
| Integrations (native) | 500+ | 1,700+ | 7,000+ |
| Branching & loops | First class | First class | Basic (paths, limited loops) |
| Error handling | Per-node retries, error workflows, code-level control | Native error routes per module | Retry + zap history dashboard |
| AI / LLM nodes | OpenAI, Anthropic, vector DBs, agents, MCP, custom code | OpenAI, Anthropic, agents | OpenAI, Anthropic, copilot, agents |
| Git / version control | Yes (JSON exports, native git in Enterprise) | Limited (change history) | Limited (version history) |
| Learning curve | Medium–high | Medium | Low |
| Best for | Engineer-owned production systems | Ops teams shipping complex flows without infra | Non-technical users, quick wins |
Pros and cons of each
- Best for
- Engineer-owned production automation, AI workflows with strict schemas, self-hosted or hybrid deployments.
- Pricing
- Community edition free (self-host). Cloud from ~$24/mo. Enterprise custom (SSO, RBAC, external secrets, git).
- Own the runtime and the data end-to-end.
- Lowest cost at scale, no per-task metering on self-host.
- Code nodes escape the visual layer when a step needs real logic.
- Strong AI stack: OpenAI, Anthropic, vector DBs, agents, MCP.
- Workflows are portable JSON, version them in git.
- Self-hosting needs a competent engineer for uptime, upgrades and backups.
- Native integration catalogue smaller than Zapier.
- Cloud plans price per active workflow, which surprises heavy users.
- Best for
- Ops teams with moderately complex workflows who do not want to touch infrastructure.
- Pricing
- Free 1,000 ops / month. Core from ~$9/mo. Pro from ~$16/mo. Teams from ~$29/mo.
- Best visual builder for iteration and branching among the three.
- First-class error routes, catch by error type, push to review queues.
- Cheaper than Zapier at comparable volumes.
- Broad integration coverage.
- Cloud only, no self-hosting.
- Operation counting can be opaque; scenarios balloon in cost with retries.
- Weaker code / custom logic story than n8n.
- Best for
- Non-technical users, quick single-purpose Zaps, teams already living inside a SaaS stack.
- Pricing
- Free 100 tasks / month. Professional from ~$29.99/mo (750 tasks). Team from ~$103.50/mo. Company custom.
- Largest integration catalogue on the market (7,000+ apps).
- Fastest time to a first working automation.
- Solid AI copilot for non-engineers.
- Deep documentation and community answers.
- Most expensive at production volume by a wide margin.
- Weakest error handling of the three.
- Limited branching, no meaningful loops on lower tiers.
- No self-hosting, no code-level control.
How they actually differ
Zapier is the widest integration surface on the market, and the friendliest onboarding. It is designed so a non engineer can wire two SaaS apps together in ten minutes. That surface comes with per task pricing that adds up fast, limited branching, and modest control over error handling.
Make (formerly Integromat) sits in the middle. The visual builder is stronger than Zapier for anything with branching, iteration, or data shaping. Pricing is per operation, cheaper than Zapier at similar volume. Integration coverage is broad but not always as polished.
n8n is the most engineer friendly of the three. Every workflow is a graph you can version in git. It runs self hosted on your own infrastructure (DigitalOcean, Hetzner, AWS) with no per execution fee, or on n8n Cloud if you want the hosted version. Code nodes make it possible to escape the visual layer when a step needs real logic.
Cost at production volume
At low volume, cost is not the story. All three land under £50 a month for hobby traffic. The gap opens up once a workflow runs thousands of times a day.
A pipeline running 50,000 executions a month costs roughly $700 to $1,000 on Zapier, $200 to $400 on Make, and around $20 to $60 of infrastructure on self hosted n8n. Once you factor in retries, error paths, and multi step branches, the multiplier gets worse for the metered platforms.
The trade off is real. Self hosted n8n needs an engineer who can keep a Docker container alive. That engineer costs money too. The break even usually lands somewhere between 10,000 and 30,000 monthly executions.
AI features in each
n8n ships AI nodes for OpenAI, Anthropic, and vector databases, plus an agent framework and MCP support. Because you can drop into a code node any time, adding a bespoke LLM call, tool, or evaluation step is straightforward.
Make and Zapier both ship AI actions and 'agents' features. They are fine for drafting, classification, and simple tool use. They are harder to bend when a project needs strict output schemas, prompt versioning, or a custom guardrail layer.
For anything that has to be reliable on real traffic (voice AI backends, phone based intake, ticket triage with billing consequences), n8n plus a hand rolled prompt layer is what actually ships.
Which one to pick
Zapier: a founder or ops lead needs a working automation this week, integration coverage matters more than cost, and volume is modest.
Make: the team has one person who enjoys the visual builder, workflows are moderately complex, and the business does not want to touch infrastructure.
n8n: automation is core to how the business runs, you want to own the runtime and the data, and there is at least one engineer who can keep a small server healthy. Self hosted is the default for production. n8n Cloud is a fair middle ground when self hosting is off the table.
Reliability and error handling
Zapier's error handling is the weakest of the three. Failed tasks retry a handful of times, then land in a dashboard that no one checks. Building a real dead letter pattern requires a second Zap and a lot of discipline.
Make has proper error routes as first class citizens. You can wire a failure branch into any module, catch by error type, and push to a review queue. This alone justifies Make over Zapier for anything that touches money or customers.
n8n gives you the most control. Every workflow can have an error workflow attached, retries are configurable per node, and because you can drop into code, patterns like idempotency keys, exponential backoff, and circuit breakers are straightforward. This is the single biggest reason production systems end up on n8n.
Migration paths
Zapier to n8n is a common move. The mental model is similar enough that a team fluent in one picks up the other in a week. Integrations map cleanly for the top fifty apps. The hard part is not the migration, it is redesigning workflows to use n8n's stronger primitives instead of porting Zapier shaped Zaps.
Make to n8n is easier still. Both are graph based, both handle iteration and branching well, and Make users are already thinking in operations per run. The main upgrade is git versioning and self hosting.
Do not migrate for the sake of it. Migrate when a single workflow is costing more than a small server, or when a business needs data residency or offline capability that a hosted platform cannot offer.
- ·Zapier wins on breadth and speed. Make wins on visual power at fair cost. n8n wins on ownership and cost at scale.
- ·Break even for self hosted n8n usually sits between 10,000 and 30,000 monthly executions.
- ·For production AI features, n8n plus a hand rolled prompt layer is the most durable stack in 2026.
- ·Migrate only when a workflow's monthly bill exceeds the cost of a small server, or when data residency requires it.
Frequently asked
Is n8n really free?+
The community edition is free and can be self hosted. n8n also sells a Cloud plan and an Enterprise plan. Both are paid. The 'free' version is only free if you value the engineering time to run it at zero.
Can Zapier or Make replace n8n for AI workflows?+
For drafting, classification, and simple tool use, yes. For anything with strict output schemas, prompt versioning, or a custom guardrail layer, they get expensive and awkward before they get impossible.
How hard is it to self host n8n?+
For a competent engineer, an afternoon on DigitalOcean with Docker Compose and a managed Postgres. Keeping it healthy long term means monitoring, backups, and a plan for upgrades. Not hard, but not zero.
What about newer tools like Windmill, Trigger.dev, or Inngest?+
Good tools, different shape. Windmill is closer to a script runner with a visual layer. Trigger.dev and Inngest are code first job runners. For anyone who needs a visual builder that non engineers can read, n8n is still the practical middle ground.
Do any of these have a mobile app or offline mode?+
None of them offer meaningful offline execution. All three assume a live internet connection and an always on webhook receiver. Self hosted n8n is the closest to offline capable, but that means running it inside your own network, not on a laptop.
How do I handle secrets and API keys safely?+
All three support environment variables and credential stores. On self hosted n8n, use a secrets manager (Doppler, Infisical, or the platform's own encrypted store) and never paste keys into workflow JSON. On Zapier and Make, rotate keys quarterly and give each Zap or scenario a scoped key where possible.
Further reading and references
Related work on this site, and the tools and profiles referenced above.
