Make vs n8n for Small Business (2026): Pricing, AI Agents, Self-Hosting, and Workflow Fit

Make is the better default for most nontechnical small businesses; n8n is the better fit for technical teams that value execution-based billing, code-level flexibility, or self-hosting. Make is faster to hand to an operations team, but its credit bill grows with the number of module actions and some AI usage. n8n charges its hosted plans by completed workflow execution rather than by step, which can favor long, complex workflows, but its editor and deployment choices demand more technical ownership.

The choice changes when governance enters the picture. Make puts team roles on Teams and advanced controls on Enterprise. n8n puts SSO, environments, and Git-based version control on its self-hosted Business plan, while its free Community edition omits several collaboration and governance features. Self-hosting n8n can improve infrastructure control; it does not remove patching, backups, monitoring, incident response, or model-provider bills.

Make generally optimizes for fast visual delivery; n8n generally offers more technical control, including a self-hosted path.

Make vs n8n: the short verdict

Neither product wins every cost comparison. Make usually wins on ease and low entry price. n8n can win economically when one execution contains many actions, but n8n Business is a substantial paid self-hosted tier—not a cheap hosting add-on.

How pricing works in 2026

Make bills primarily in credits; n8n bills paid plans primarily in workflow executions. That difference matters more than the headline subscription price.

Make’s documentation says most non-AI modules consume one credit per operation. A workflow that checks an order, looks up a customer, updates a CRM, sends a message, and writes a log can consume several credits for one business event. Make’s own AI Provider introduces dynamic token-based credit use in addition to operations for AI Agents and other built-in AI tools. With a custom AI-provider connection on a paid plan, Make charges operational credits while the model provider bills token usage separately.

n8n says a paid-plan production workflow counts once when the workflow runs from start to finish, regardless of how many steps it contains. Sub-workflows can affect counting rules, and retries or workflow design can still change real consumption, so estimate from production architecture rather than node count alone.

Make usually meters standard module actions; n8n paid plans meter completed production workflow executions.

Current public starting prices

Prices below were verified from vendor pages on August 18, 2026. They exclude taxes, currency conversion, model-provider charges, implementation labor, and overages.

Make’s tier selector scales beyond 10,000 credits. For example, Core currently lists 40,000 credits at $34.12 month-to-month or $29/month billed annually, and 150,000 credits at $116.47 or $99. n8n’s public cards show annual-billing baselines; verify the checkout or quote for other execution volumes and monthly terms.

Realistic light, moderate, and high-volume cost scenarios

Estimate business events first, then translate them into each vendor’s billing unit. Comparing 10,000 Make credits with 10,000 n8n executions is usually nonsense: one is roughly an action allowance for most standard modules, while the other is a full workflow-run allowance.

These are planning examples, not forecasts. Make routers, iterators, retries, polling, file processing, and AI tokens can change credit use. n8n workflow structure, retries, sub-workflows, concurrency, infrastructure, and paid feature requirements can change cost. A fair proof of concept runs two representative workflows for at least one full business cycle and records both usage units and labor.

Make and n8n differ most on workflow fit

Make is optimized for visual assembly by business operators; n8n is optimized for technical flexibility without forcing every workflow into conventional code. Both have visual canvases, webhooks, API calls, branching, data transformation, and large integration libraries. The practical difference is how quickly a team reaches the edge of the visual layer.

Choose Make when the work is mostly moving data among mainstream SaaS applications, applying filters, formatting fields, and notifying people. It is especially strong when operations staff need to understand the flow without owning a runtime.

Choose n8n when workflows need JavaScript or Python steps, custom API behavior, custom nodes, private-network services, or sophisticated error handling. Its execution-based billing also reduces the incentive to compress a complex workflow merely to save billable steps.

Make’s limitation is that complex scenarios can become visually dense and credit-heavy. n8n’s limitation is that flexibility creates more ways to build something fragile. A canvas full of code nodes is still software; the rounded boxes do not negotiate with entropy.

Deterministic automation is not the same as an AI agent

Use deterministic workflows for rules you can define; use agents only when the task genuinely requires interpretation or tool selection. A deterministic workflow follows known branches: when an invoice is overdue, look up the account owner and send a templated reminder. An agent may interpret an unstructured request, choose among tools, retrieve context, and decide what action to take.

Both platforms can combine the two approaches. Make AI Agents can call scenario tools and use Make’s AI Provider or a custom provider. Make documents one operational credit plus token-based credits when an agent runs with Make’s provider; tool calls add their own operation use. Custom provider connections on paid plans shift token charges to the model vendor.

n8n provides AI Agent and model nodes that connect to providers such as OpenAI or Anthropic. n8n plan AI credits refer to its AI Assistant feature, not a blanket allowance for every third-party model call in production workflows. Production model credentials generally create separate provider bills.

For either platform, agents add nondeterminism, prompt and model maintenance, token cost, latency, evaluation work, and new failure modes. Keep payments, deletions, permissions, and legally significant actions behind deterministic validation or human approval.

What self-hosting n8n actually requires

Self-hosting n8n replaces vendor infrastructure work with your infrastructure work. The free Community edition can be appropriate for an owner-operated internal system, but “free” describes the software subscription—not the service you must run.

A production owner needs to cover:

• a supported deployment, domain, TLS, and network controls;
• a durable database, encrypted credential handling, and secret rotation;
• backups plus tested restoration, not merely snapshots that nobody has restored;
• n8n upgrades, dependency and host patching, and release compatibility checks;
• monitoring for failed workflows, queue growth, disk use, memory pressure, and expired credentials;
• execution-data pruning and retention settings;
• scaling and concurrency design, including workers and Redis if queue mode is used;
• incident response, audit evidence, and business continuity;
• model-provider accounts, rate limits, spend controls, and data-processing terms.

n8n’s free Community edition omits paid features including SSO, environments, external secrets, Git version control, multi-main operation, projects, and workflow or credential sharing. Registered Community adds a smaller set of free features such as folders, debug-in-editor, and custom execution data. The Sustainable Use License permits many internal business uses, but it is not a standard open-source license and restricts uses such as offering n8n itself as a competing hosted service. Have counsel review unusual redistribution or commercial-service models.

Self-hosting adds control by making your team responsible for the runtime, data, secrets, backups, updates, monitoring, and incidents.

Concurrency, retention, collaboration, and governance

The cheaper plan can be the wrong plan if it cannot meet peak throughput or control requirements. n8n’s current Cloud limits are explicit: Starter allows five concurrent production executions and Pro allows 20; additional runs queue in FIFO order. Enterprise lists 200-plus. Its comparison table lists saved-execution caps of 2,500 on Starter, 25,000 on Pro, and 50,000 on Enterprise, with maximum execution-log retention of seven days, 30 days, and unlimited respectively. “Insights” retention is a separate analytics concept from execution-log retention.

Make’s public plan table emphasizes priority execution on Pro and parallel scenario execution as a higher-tier capability rather than publishing a simple universal concurrency number. Buyers with bursty webhooks should ask Make to document expected queueing, rate limits, webhook capacity, and recovery behavior for the selected credit tier.

For collaboration, Make Core is mainly an individual paid workspace; Teams adds team roles and shared templates. Enterprise adds controls such as SSO/domain management and advanced support. n8n Starter includes one shared project and unlimited users; Pro adds three shared projects and admin roles. Business adds six shared projects, SSO/SAML/LDAP, environments, and Git version control. Enterprise adds unlimited shared projects, external secret-store integration, log streaming, extended retention, and an SLA.

No plan badge makes a workflow compliant. Regulated buyers still need to verify deployment region, subprocessors, encryption, access reviews, audit exports, retention, deletion, incident terms, and whether AI providers receive regulated data.

Which platform fits your small business?

Choose Make for speed; choose n8n for control—unless the control requires skills your business does not actually have.

Choose Make if

• business operators will build and maintain common SaaS workflows;
• you want managed infrastructure and a low starting subscription;
• fast visual debugging matters more than code-level extensibility;
• most workflows are short to moderate in action count;
• shared templates and role separation on Teams meet your governance needs.

Choose n8n if

• a technical owner can review code, APIs, credentials, and failures;
• workflows are long enough that per-execution billing is attractive;
• you need custom nodes, private services, or self-hosting;
• you accept the operational cost of Community edition or can justify Business/Enterprise;
• environments, Git-backed change control, external secrets, or log streaming are selection criteria.

For regulated workflows

Start with a written controls matrix, not a feature demo. If self-hosting is mandatory and the team can operate it, n8n deserves the first evaluation. If managed deployment is preferred, compare Make Enterprise with n8n Cloud Enterprise and require contractual answers. Keep high-risk AI actions gated until model providers, data retention, and human review are approved.

Migration and hidden-cost checklist

Migration cost is mostly in workflow behavior, not canvas recreation. Before switching, inventory:

• triggers, schedules, webhooks, and peak arrival rates;
• every app connection, credential owner, scope, and rotation process;
• Make credit use by module and n8n execution design by workflow;
• iterators, retries, polling, error routes, sub-workflows, and idempotency;
• custom code, unsupported integrations, community nodes, and API limits;
• data stores, files, execution history, logs, and required retention;
• AI prompts, models, tools, knowledge sources, evaluations, and token bills;
• users, projects, roles, approval steps, SSO, and audit requirements;
• dev/test/prod separation and rollback method;
• parallel-run period, reconciliation checks, cutover owner, and rollback trigger;
• hosting, database, backups, observability, on-call time, and security reviews;
• training, documentation, consultant fees, and the cost of whoever becomes “the automation person.”

Run old and new workflows in parallel where duplicate side effects can be prevented. Compare outputs, failure rates, latency, usage, and maintenance time before cutover.

Methodology and limitations

This comparison is an editorial synthesis verified against first-party Make and n8n pricing, billing, AI, deployment, and plan documentation on August 18, 2026. It is not based on hands-on product testing. Public prices are starting points, may vary by currency or volume, and can change. Enterprise capabilities and compliance suitability require written vendor confirmation. Google Search Console and GA4 evidence was unavailable, so no first-party traffic or conversion claim is made.

Frequently asked questions

Is Make cheaper than n8n?

Make has the lower public managed entry price in the scenarios above. n8n can become economically attractive when workflows contain many steps because paid plans meter full workflow executions rather than each node, but governance tiers and self-hosting labor can outweigh that advantage.

Is n8n really free if self-hosted?

n8n Community software can be used free indefinitely for many internal business purposes. Hosting, databases, backups, upgrades, monitoring, security, and staff time are not free, and several collaboration or governance features require paid editions.

Which is easier for beginners, Make or n8n?

Make is generally easier for nontechnical beginners building mainstream SaaS automations. n8n is approachable for a visual development tool, but its strongest advantages appear when the user understands APIs, data structures, code, and infrastructure.

Which is better for AI agents?

Neither wins universally. Make offers a managed AI-provider path and visual tool calling; n8n offers broad model-node flexibility and technical control. Choose based on approval controls, model-provider policy, evaluation needs, and workflow ownership—not an “AI agent” label.

Can n8n self-hosting guarantee compliance?

No. Self-hosting provides infrastructure control, not automatic compliance. Your organization becomes responsible for configuration, access, retention, patching, monitoring, evidence, and incident response.

Can I migrate Make scenarios directly into n8n?

Not as a reliable one-click conversion. Rebuild and test triggers, mappings, branches, retries, credentials, and error handling. Treat migration as behavior verification, not visual translation.