If you are picking a workflow automation platform for an enterprise team in 2026, you have three serious candidates: n8n, Zapier, and Make (formerly Integromat). This post compares them across the dimensions that actually decide the choice — not feature counts, but the operational, financial, and compliance properties that matter at scale.

This is what we recommend to clients running real automation programmes. We have shipped production workflows on all three platforms.

The headline summary

Platform	Best for	Watch out for
n8n (self-hosted)	EU/MENA data residency, custom logic, AI integration, large workflow counts	Operational ownership; you run the infrastructure
Zapier	Marketing / SaaS-ops teams, fast-shipping, broadest integration catalogue	Cost scales steeply with task volume; weaker on AI
Make	Visual-heavy users, complex branching, generous free tier	Slower runtime than n8n; smaller catalogue than Zapier

If you are an Egyptian or MENA enterprise with data-residency requirements (CBE financial-services AI rule, SAMA data localisation), n8n self-hosted on a sovereign-cloud or local VPS is almost always the right answer. The rest of this post explains why.

The dimensions that actually matter

1. Data residency

The single biggest decider in 2026 for MENA enterprises. Where does the data sit?

n8n self-hosted: anywhere you put the box. Hetzner Frankfurt, OVH Marseille, Etisalat UAE — all viable. For CBE-licensed entities, this is the only way to keep workflow data inside Egypt.
n8n Cloud: EU-only (Frankfurt). Acceptable for non-regulated workloads.
Zapier: US-default, with EU data zones available on the Enterprise tier. No MENA option.
Make: Czech Republic + US. No MENA option.

For most regulated workloads in MENA, this dimension alone rules out cloud-hosted Zapier and Make. If you are a non-regulated SaaS company, the difference is less urgent.

2. AI integration

The platforms have rapidly diverged on AI quality in 2026:

n8n: native nodes for OpenAI, Anthropic, Mistral, Cohere, Replicate, ElevenLabs, plus a generic “AI Agent” node that ties to LangChain. Best ergonomics for multi-step LLM workflows. Built-in support for tool calling, structured output, streaming.
Make: solid OpenAI and Claude integrations. AI Builder feature lets you visually compose prompt chains. Adequate, not best-in-class.
Zapier: has improved with “AI Actions” but still requires more glue than the others. Most AI-heavy users we know route Zapier triggers into a webhook that hits n8n or a custom worker.

If your workflows are AI-heavy (LLM-driven triage, content generation, summarisation), n8n wins decisively. For light AI use (occasional sentiment analysis or summary), all three are fine.

3. Pricing at scale

We model pricing in dollars per 100K monthly task executions, which is the metric that matters for enterprises:

Tasks/mo	n8n self-hosted	n8n Cloud	Zapier (Team)	Make (Pro)
10K	~USD 30 (VPS)	USD 50	USD 19	USD 16
100K	~USD 30	USD 250	USD 299	USD 99
1M	~USD 50 (bigger VPS)	USD 1,500	USD 1,200+	USD 700+
10M	~USD 200 (orchestrated cluster)	enterprise-quote	enterprise-quote	enterprise-quote

Note: pricing changes monthly; the table above reflects May 2026 list prices. n8n self-hosted scales linearly with compute; the cloud options scale linearly with task count.

At 100K+ tasks/month, n8n self-hosted is dramatically cheaper. The trade-off is operational ownership — someone on your team needs to maintain the box. For most enterprises, the answer is “yes, that is worth saving USD 200+/month.”

4. Workflow ergonomics

This is the dimension where the platforms diverge most by personality:

Zapier: linear “Trigger → Action → Action” model. Easiest for non-technical users. Strong for marketing-ops, simple SaaS-glue. Weakest at conditional logic and loops.
Make: visual canvas with branching, iterators, error routes. Strongest for users who think visually. Slower to execute than n8n.
n8n: visual canvas + JavaScript escape hatch on every node. Strongest for technical users. Steepest learning curve.

For a non-technical marketer building a 5-step Slack-to-Notion sync, Zapier is faster. For a sales-ops engineer building a 30-step pipeline with conditional branches and AI calls, n8n is the only one that does not fight you.

5. Integration catalogue

Zapier: ~7,000 native integrations. Largest in the industry.
Make: ~2,000 native integrations.
n8n: ~1,200 native integrations + a generic HTTP node that connects to anything with an API + a JavaScript node that runs arbitrary code.

The headline count favours Zapier, but in practice the “long tail” integrations Zapier offers are rarely used. The 200-300 you actually use exist on all three platforms.

6. Self-hosting

n8n: first-class self-hosting story. Docker image, Helm chart, Kubernetes operator. This is the differentiator.
Make: no self-hosting.
Zapier: no self-hosting.

For any enterprise with even moderate data-residency requirements, self-hosting tips the scales toward n8n by a wide margin.

Decision framework

We use this matrix when advising clients:

Is data residency a hard requirement?              → n8n self-hosted
Is AI-heavy workflow the primary use case?         → n8n
Is the user a non-technical marketer?              → Zapier or Make
Is task volume > 100K/month?                       → n8n self-hosted (cost)
Does the team think visually about workflows?      → Make
Is the integration catalogue the deciding factor?  → Zapier

For a typical MENA enterprise running mixed workloads — marketing automation + sales ops + customer support — the right answer is almost always:

n8n self-hosted as the workhorse for AI-heavy and regulated workloads
Zapier or Make for the marketing team’s quick-win workflows where speed and integration breadth matter more than cost or residency

This “two-platform” model is common at the USD 5M+ ARR scale. The cost overhead of running two platforms is offset by giving each team the right tool.

What to do next

If you are picking a platform for the first time:

List your top 10 actual workflows. Not the ones you might build; the ones you will build in the next 90 days.
Score each workflow against each platform on three criteria: ease of build, ongoing cost, data residency.
Pick the platform that wins majority for real workflows.

If you are already running workflows and want to evaluate a migration: usually the answer is “stay” unless cost, residency, or AI capability is a real blocker. Migration is expensive; the right time to switch is when one of these dimensions becomes a hard constraint.

If you would like us to run this evaluation for your team, contact us at contact@kalastor.net — typical engagement is 2 weeks to a recommended stack with a migration plan.

Disclosure: Kalastor consultants have shipped production workflows on all three platforms across a range of clients. We do not have a commercial relationship with any of the three vendors.