Zapier vs Make vs n8n: Complete Comparison

Overview

Zapier, Make (formerly Integromat), and n8n are the three most widely adopted workflow automation platforms (as of January 2026). Each takes a fundamentally different approach to automation: Zapier prioritizes simplicity and breadth of integrations, Make emphasizes visual workflow design with granular control, and n8n offers an open-source, self-hostable platform with code-level flexibility. This comparison evaluates all three across 15 dimensions to help identify which platform fits specific requirements.

Platform Backgrounds

Zapier was founded in 2011 by Wade Foster, Bryan Helmig, and Mike Knoop. Headquartered in San Francisco, it operates as a fully remote company. Zapier raised $1.4 billion in a 2024 secondary sale that valued the company at $5 billion. It remains the largest automation platform by user count, with over 2.2 million customers reported in company communications.

Make was originally launched as Integromat in 2012 by a team in Prague, Czech Republic. Celonis acquired Integromat in 2020 and rebranded it as Make in 2022. Make has grown significantly under Celonis ownership, expanding from approximately 500,000 users at acquisition to over 1.5 million by early 2025.

n8n was founded in 2019 by Jan Oberhauser in Berlin, Germany. The platform is source-available under a sustainable-use license (changed from a fair-code model in 2024). n8n raised $12 million in Series A funding in 2022. The platform is available as both a self-hosted Community Edition and a managed cloud service (n8n Cloud).

Feature Comparison Table

Pricing at Scale

Pricing is the area where these three platforms diverge most significantly. The unit of measurement differs for each, making direct comparison require normalization.

Pricing Tiers (as of January 2026)

Zapier:

• Free: 100 tasks/month, 5 single-step Zaps
• Professional: $19.99/month (750 tasks, multi-step Zaps)
• Team: $69/month (2,000 tasks, shared workspaces)
• Enterprise: Custom pricing

Make:

• Free: 1,000 operations/month, 2 active scenarios
• Core: $9/month (10,000 operations)
• Pro: $16/month (10,000 operations + advanced features)
• Teams: $29/month (10,000 operations + team features)
• Enterprise: Custom pricing

n8n:

• Community (self-hosted): Free, unlimited executions
• Starter (cloud): $20/month (2,500 executions)
• Pro (cloud): $50/month (10,000 executions)
• Enterprise: Custom pricing

Cost Comparison at Different Volumes

To normalize costs, consider a standard workflow with 5 steps processing varying record volumes per month:

The critical difference: Zapier counts each step as a task, so a 5-step workflow consumes 5 tasks per record. Make counts each module execution as an operation, similar to Zapier. n8n counts workflow executions, not individual steps, so a 5-step workflow processing one record uses just one execution.

At 100,000 records per month with a 5-step workflow, the annual cost difference between Zapier ($8,400/year) and n8n self-hosted ($240/year) exceeds $8,000. This gap widens further with more complex workflows.

Hidden Pricing Factors

• Zapier premium apps: Certain integrations (Salesforce, HubSpot CRM, databases) require the Professional plan or higher
• Make data transfer: Large payloads consume additional operations; a 10 MB file download counts as more than a simple API call
• n8n Cloud fair use: The cloud plans include fair-use limits on execution time and data transfer that may apply to very long-running or data-heavy workflows
• All platforms: Webhook-triggered automations that receive high volumes of external events can consume quotas faster than scheduled workflows

Ease of Use

Learning Curve

Zapier has the lowest barrier to entry. The step-based builder presents a linear sequence: "When this happens, do this, then this." New users can build a working automation in 15-20 minutes. The constraint is that complex branching and looping require workarounds or are not supported.

Make uses a visual canvas where modules are connected by lines. This is more powerful than Zapier's linear model but requires understanding concepts like routers (for branching), iterators (for loops), and aggregators (for combining data). Most users need 1-2 hours to feel comfortable. The visual representation of data flow is clearer for complex workflows.

n8n uses a visual canvas similar to Make. The learning curve is comparable to Make for no-code usage. However, n8n's code nodes add a dimension that requires programming knowledge to use. For teams that include developers, this is an advantage; for purely non-technical teams, the extra complexity can be intimidating even if unused.

Workflow Builder Comparison

Integration Coverage

Breadth vs Depth

Zapier's 7,000+ integrations give it the broadest coverage. For niche SaaS applications, Zapier is most likely to have a pre-built connector. Make's 1,800+ integrations cover most mainstream applications but may lack connectors for industry-specific tools. n8n's 400+ built-in nodes cover the most common services, and its HTTP Request node and community node ecosystem fill many gaps.

Connector Quality

Raw integration counts are misleading. A connector that only supports "create record" and "get record" is less useful than one supporting triggers, searches, creates, updates, deletes, and batch operations.

Zapier connectors are typically maintained by the third-party app developers themselves through Zapier's developer platform. Quality varies: major apps (Slack, Google Sheets, Salesforce) have comprehensive connectors; smaller apps may support only basic operations.

Make connectors are primarily built and maintained by Make's internal team. This results in more consistent quality but slower coverage of new applications. Make's custom app builder allows users to create connectors for unsupported services.

n8n nodes are built by the core team and the open-source community. Community-contributed nodes are available through the n8n community nodes repository. The quality of community nodes varies. n8n's declarative node creation system (added in 2024) simplified building custom nodes.

Integration Coverage by Category

Self-Hosting Options

Self-hosting is the defining differentiator between n8n and its competitors.

n8n Self-Hosting

n8n supports deployment via Docker, Docker Compose, and Kubernetes. The Community Edition is free to use with no execution limits.

Minimum requirements (as of January 2026):

• 2 vCPU, 4 GB RAM for small to medium workloads
• PostgreSQL database (recommended over SQLite for production)
• Persistent storage for workflow data and execution logs

Scaling options:

• Queue mode: Distributes executions across multiple worker instances
• Separate webhook processor: Dedicated process for handling incoming webhooks
• External database: PostgreSQL for workflow storage and execution data

Operational considerations:

• Updates require pulling new Docker images and restarting
• No automatic security patches (manual update cycle)
• Backup responsibility falls on the operator
• Monitoring and alerting must be configured separately

Zapier and Make

Neither Zapier nor Make offers self-hosting. Both are cloud-only SaaS platforms. For organizations with strict data residency or air-gap requirements, this is a disqualifying factor.

ActivePieces and Pipedream as Alternatives

For teams wanting self-hosting with a Make-like experience, ActivePieces offers a similar visual builder with Docker-based self-hosting and an open-source core. Pipedream provides a cloud platform with a generous free tier and full Node.js runtime access, though it does not support self-hosting.

Advanced Features

AI and Machine Learning

All three platforms have added AI features, but the implementations differ:

• Zapier offers AI actions that can summarize text, extract data, and classify content. It also uses AI for suggested field mappings during workflow configuration.
• Make includes AI modules for OpenAI, Anthropic, and other providers, enabling text generation, image analysis, and embeddings within workflows.
• n8n provides an AI Agent node with LangChain integration, supporting tool-use agents, retrieval-augmented generation (RAG), and chaining multiple AI operations. This is the most developer-oriented AI implementation of the three.

Workflow Management

Error Handling

Zapier provides automatic retry for failed steps (up to 3 attempts) and error notifications via email. There is no per-step error routing.

Make offers the most granular error handling of the three. Each module can have a dedicated error route with options to break, resume, ignore, rollback, or commit. Error routes can contain multiple modules for complex recovery logic.

n8n supports per-node error workflows. When a node fails, execution can route to a separate error-handling branch. Combined with code nodes, this enables custom retry logic, dead-letter queues, and conditional error recovery.

When to Choose Each Platform

Choose Zapier When

• The team has no technical experience and needs the simplest possible interface
• Automations are primarily linear (trigger, then 1-5 sequential actions)
• Integration with niche or industry-specific SaaS applications is required
• The organization prefers a fully managed service with zero infrastructure concerns
• Budget allows for per-task pricing at the expected volume

Choose Make When

• The team benefits from visualizing workflow logic as a diagram
• Workflows require branching, looping, or aggregation logic
• Cost-efficiency per operation matters (Make is typically 3-5x cheaper than Zapier at scale)
• The team is comfortable with a moderate learning curve
• Complex error handling with per-module error routes is needed

Choose n8n When

• Self-hosting is required for data sovereignty, compliance, or cost reasons
• The team includes developers who can use code nodes for complex logic
• High-volume processing makes per-execution pricing (rather than per-step) important
• Git-based version control for workflows is a requirement
• The organization wants to avoid vendor lock-in with an open-source core
• AI agent workflows with LangChain integration are part of the roadmap

Migration Considerations

Moving from Zapier to Make

There is no automated migration path. Workflows must be manually recreated. The mapping is relatively straightforward because both platforms use a visual builder with similar concepts (triggers, actions, filters). Main differences to account for: Zapier Paths become Make Routers; Zapier Formatter steps become Make text/math/date functions; Zapier's Code by Zapier becomes Make's custom JavaScript module.

Moving from Zapier to n8n

Manual recreation is required. n8n provides documentation mapping Zapier concepts to n8n equivalents. The main challenge is re-establishing all API credentials in n8n and updating external webhook URLs. Workflows with more than 3 steps typically translate well to n8n's canvas because n8n's branching and looping capabilities are more expressive than Zapier's.

Moving from Make to n8n

Manual recreation is required. The visual canvas model is similar between Make and n8n, so the conceptual translation is straightforward. Make's Routers map to n8n's IF/Switch nodes; Make's Iterators map to n8n's Loop nodes; Make's error routes map to n8n's error workflows.

Lock-In Risk Assessment

Conclusion

Zapier, Make, and n8n serve overlapping but distinct segments of the automation market. Zapier is the broadest and simplest platform, suited to non-technical users who need wide integration coverage. Make offers a balance of visual power and cost-efficiency that fits teams ready to invest in a moderate learning curve. n8n provides the most flexibility and lowest long-term cost for organizations with technical capability and a preference for self-hosting or open-source software. The right choice depends on the specific combination of team skills, integration requirements, compliance needs, and budget constraints.