Zapier vs Make vs n8n (2025): The Definitive Comparison — Pricing, Features, and Decision Matrix

Choosing the wrong automation platform is an expensive mistake. You invest hours learning the interface, building workflows, connecting systems—and then discover that pricing is unsustainable, a critical feature is missing, or scaling means starting over. Gartner estimates that by 2025, 70% of new applications built by enterprises will use low-code or no-code technologies, up from less than 25% in 2020. The market is growing fast, but the three dominant players—Zapier, Make, and n8n—serve fundamentally different needs. This guide gives you the complete picture: real pricing at every tier, feature-by-feature analysis, learning curve assessment, and a clear decision matrix so you choose the right tool the first time.

The short answer

Before the deep dive, here is the executive summary:

• Zapier: Best for speed-to-value. Largest app library (7,000+). Simplest interface. Highest cost at scale. No self-hosting. Choose when simplicity matters more than cost.
• Make (formerly Integromat): Best balance of power and usability. Strong visual builder. Better pricing at medium-to-high volume. EU data centres. Choose when you need complex logic without writing code.
• n8n: Best for control. Open-source, self-hostable. Fixed infrastructure cost regardless of volume. Choose when you need data sovereignty, unlimited executions, or you are an agency serving multiple clients.

If that is enough to decide, go ahead. If you want the full evidence, read on.

Pricing comparison: the real numbers in 2025

Pricing is the single biggest factor in long-term platform choice. All three tools use different pricing models, and the difference in annual cost can be thousands of dollars at moderate volume. Here is how each one works.

Zapier pricing

Zapier charges per task. A task is a single action step that executes successfully. A five-step Zap that runs once consumes five tasks. This distinction matters enormously—a workflow with 10 steps running 100 times per month uses 1,000 tasks, not 100.

| Plan | Monthly price | Tasks/month | Multi-step Zaps | Premium apps | |---|---|---|---|---| | Free | $0 | 100 | No (2-step only) | Limited | | Professional | $29.99 | 750 | Yes | Yes | | Professional | $49.99 | 2,000 | Yes | Yes | | Team | $103.50 | 2,000 | Yes | Yes (shared) | | Enterprise | Custom | Custom | Yes | Full |

Additional tasks above plan limits cost approximately $0.01–0.03 per task depending on your tier. The key gotcha: multi-step workflows multiply task consumption quickly. A 7-step Zap running 500 times/month consumes 3,500 tasks—already above the Professional plan. At the Team tier, you are paying roughly $0.05 per task. At 50,000 tasks/month, that is $2,500/month on Zapier.

Zapier also introduced Zapier Tables (a simple database), Zapier Interfaces (form and page builder), Zapier Chatbots, and Zapier Canvas (a visual planning tool). These add value but are designed to lock you further into the ecosystem. Zapier Central, their AI agent feature, is available in beta and allows natural-language workflow creation. See Zapier pricing for current figures.

Make pricing

Make charges per operation. An operation is a single module execution within a scenario. This is similar to Zapier's task model, but Make's operations tend to be more granular—a router module that splits into three paths counts as one operation, while the three downstream modules count as three more.

| Plan | Monthly price | Operations/month | Data transfer | Active scenarios | |---|---|---|---|---| | Free | $0 | 1,000 | 100 MB | 2 active | | Core | $10.59 | 10,000 | 1 GB | Unlimited | | Pro | $18.82 | 10,000 | 1 GB | Unlimited + priority | | Teams | $34.12 | 10,000 | 1 GB | Unlimited + roles | | Enterprise | Custom | Custom | Custom | Custom |

Additional operations beyond the plan limit can be purchased. The Pro plan adds custom variables, full-text execution log search, and priority execution. The crucial difference from Zapier: Make's base plans include 10,000 operations at $10.59/month. The same volume on Zapier's Professional plan costs $49.99/month. At 50,000 operations/month, Make costs roughly $50–70/month depending on add-on packs. The same volume on Zapier would exceed $150/month.

Make offers EU data centres (Frankfurt), which matters for GDPR compliance. Their visual scenario builder renders the entire workflow as a flowchart, making complex logic easier to understand and debug. See Make pricing for current tiers.

n8n pricing

n8n has a fundamentally different model. The self-hosted community edition is free and open-source under the Sustainable Use License. You pay for your server infrastructure, not for executions.

| Option | Monthly cost | Executions | Users | Data residency | |---|---|---|---|---| | Self-hosted (Community) | $0 + server ($5–25/mo) | Unlimited | Unlimited | Your server | | n8n Cloud Starter | $24 | 2,500 | 1 | n8n's cloud | | n8n Cloud Pro | $60 | 10,000 | 5 | n8n's cloud | | n8n Cloud Enterprise | Custom | Custom | Custom | Custom or your cloud |

Self-hosting is the game-changer. A $10/month VPS on DigitalOcean, Hetzner, or Railway gives you unlimited workflow executions, unlimited workflows, and complete data sovereignty. For an agency running 100,000+ executions per month across multiple clients, the cost difference is dramatic: potentially $3,000+/month on Zapier vs. $10–25/month self-hosted on n8n.

The tradeoff is operational: you manage the server, handle updates, configure backups, and troubleshoot infrastructure issues. Docker and Docker Compose make this manageable for anyone with basic DevOps knowledge. See n8n pricing and the self-hosting guide.

Cost comparison at scale

To make pricing concrete, here is what each platform costs at common volume levels (approximate, based on 2024/2025 published pricing):

| Monthly volume | Zapier (est.) | Make (est.) | n8n self-hosted (est.) | |---|---|---|---| | 1,000 executions | $29.99 | $10.59 | $5–10 (server) | | 10,000 executions | $73.50 | $10.59 | $5–10 (server) | | 50,000 executions | $250+ | $50–70 | $10–20 (server) | | 200,000 executions | $800+ | $150–200 | $15–25 (server) | | 500,000 executions | $2,000+ | $400+ | $20–30 (server) |

The pattern is clear: Zapier is the most expensive at every volume level. Make is significantly cheaper. n8n self-hosted is cheapest at scale by an order of magnitude. However, n8n requires technical capability to host and maintain.

Feature comparison: what each tool actually does

Price is only half the equation. Here is a feature-by-feature breakdown of the capabilities that matter in practice.

App library and integrations

Zapier: 7,000+ apps. The largest library by far. If an app has an API, Zapier probably has a connector. This is Zapier's strongest competitive advantage. For niche tools (industry-specific CRMs, regional payment processors, obscure project management apps), Zapier is often the only option with a native connector. Zapier's app directory is the reference.

Make: 1,800+ apps. Smaller than Zapier, but covers all major SaaS tools. Make's connectors tend to be deeper—more trigger and action options per app. Where Zapier might offer 5 actions for a given app, Make often offers 10–15, including advanced operations like batch updates and webhooks. The HTTP/Webhook module lets you connect to any API manually, which covers most gaps.

n8n: 400+ built-in nodes, plus custom nodes. The smallest native library, but this understates n8n's capability. The HTTP Request node connects to any REST API. The Code node lets you write JavaScript or Python for anything without a native connector. The community contributes custom nodes via npm. For developers, the smaller library is rarely a blocker; for non-technical users, it can be.

Workflow complexity and branching

Zapier: Paths (conditional branching) are available on paid plans. You can branch into up to three paths. Filters let you stop a Zap if conditions are not met. For straightforward if/then logic, this works. For complex decision trees with five or more branches, nested conditions, or loops, Zapier becomes unwieldy. There is no native looping—processing an array of 50 items requires workarounds or Zapier's built-in Looping feature (which consumes one task per iteration).

Make: This is where Make excels. The visual scenario builder supports unlimited branching via routers, filters on every connection, iterators (loop through arrays), and aggregators (combine results back). Error handling routes let you define what happens when a module fails—retry, ignore, send an alert, or take a different path. You can build workflows with 50+ modules, multiple parallel branches, and complex data transformations. Make's scenario builder renders this visually as a flowchart, which makes debugging straightforward.

n8n: Comparable to Make for branching, with the added advantage of the Code node for arbitrary logic. n8n supports IF nodes, Switch nodes (multi-path routing), loops via the SplitInBatches node, and merge nodes for combining data streams. The execution model is node-by-node, and you can inspect data at each step during debugging. For developers, n8n's flexibility is unmatched—you can mix no-code and code nodes freely within the same workflow.

Error handling

Zapier: Basic. If a step fails, the Zap stops and you get a notification email. You can configure "Autoreplay" to retry failed tasks, and Zapier logs errors for review. But there is no way to define alternative paths on failure (e.g., "if the CRM update fails, log to a spreadsheet and alert Slack"). For mission-critical workflows, this is a significant limitation.

Make: Strong. Every connection between modules can have an error handler attached. Options include: Resume (continue with a default value), Rollback (undo all changes in the scenario), Commit (save what worked, skip what failed), and Break (pause the scenario for manual review). You can build sophisticated error recovery—retry three times, then log to a Google Sheet, then send a Slack alert. This is essential for production workflows handling real customer data.

n8n: Excellent. Error workflows can be defined at the workflow level or the node level. You can create separate "error workflows" that trigger when any workflow fails—centralising your error handling and alerting. The retry mechanism supports configurable attempts and wait times. Combined with Code nodes, you can build error handling as sophisticated as any custom application.

Data stores and state management

Zapier: Zapier Tables is a lightweight database for storing and retrieving data across Zap runs. Useful for tracking state (e.g., "has this lead been contacted already?"), deduplication, and simple lookups. Limited in capacity and query capability compared to a real database.

Make: Data stores are a built-in feature—a simple key-value or tabular store that persists across scenario runs. Supports up to 10 MB on the free plan, scaling with paid tiers. Useful for the same state-tracking and deduplication use cases. Make also has a Data Structures feature for defining and validating complex JSON schemas.

n8n: No built-in data store, but this is by design. Self-hosted n8n can connect to any database (PostgreSQL, MySQL, MongoDB, Redis) directly via native nodes. This gives you far more storage, querying capability, and flexibility than either competitor—but requires you to manage the database. For state management across workflow runs, a simple PostgreSQL table outperforms both Zapier Tables and Make Data Stores.

AI and LLM capabilities

This is the fastest-evolving area across all three platforms. As of 2025:

Zapier: Has native OpenAI, Anthropic Claude, and Google Gemini integrations. Zapier Central (beta) lets you describe workflows in natural language and have AI build them. AI by Zapier is a built-in action that can summarise text, extract data, classify content, and generate responses without needing an external API key. Zapier is investing heavily in AI as a differentiator.

Make: Native OpenAI, Anthropic, and other LLM modules. Make's AI capabilities focus on integrating LLMs into existing scenarios—text classification, data extraction, content generation within a larger workflow. The visual builder makes it easy to see where AI fits in a multi-step process.

n8n: Has an AI Agent node, LangChain integration, and native connectors for OpenAI, Anthropic, Google Gemini, Ollama (local LLMs), and more. n8n's AI capabilities are arguably the most advanced: you can build full AI agent workflows with tool use, memory, and retrieval-augmented generation (RAG). Self-hosting also means you can run local LLMs via Ollama for complete data privacy—no data leaves your server.

Self-hosting and data sovereignty

Zapier: No self-hosting option. All data is processed on Zapier's US-based infrastructure. For businesses with strict data residency requirements (EU GDPR, healthcare HIPAA, financial regulations), this can be a dealbreaker.

Make: No self-hosting. However, Make offers EU data centres (Frankfurt), which satisfies GDPR requirements for many businesses. Enterprise plans may offer additional residency options.

n8n: Full self-hosting. You control where your data lives—your own server, your own cloud account (AWS, GCP, Azure), or a regional VPS provider. This is critical for regulated industries, government contractors, and any business handling sensitive personal data. Self-hosting also means no vendor lock-in on infrastructure—if n8n changes its licensing, your existing installation continues to work.

Learning curve and user experience

Zapier: 1–2 hours to first workflow

Zapier's interface is the simplest of the three. The trigger-action model is intuitive: "When X happens, do Y." Non-technical users (marketing, sales, operations) can build their first Zap in under an hour with no training. Zapier's documentation, university courses, and community templates are the most extensive. The tradeoff: the simplicity that makes it easy to start makes it harder to build complex logic.

Make: 3–5 hours to first workflow

Make's visual scenario builder is more powerful but requires more learning. The concepts of modules, connections, routers, iterators, and aggregators take time to understand. Most users need 3–5 hours of hands-on experimentation or one of Make's Academy courses to feel confident. The payoff is significantly more capability. Once learned, Make users rarely go back to Zapier for anything beyond the simplest flows. Make Academy provides structured learning paths.

n8n: 5–10 hours to first workflow (self-hosted)

n8n's learning curve has two parts: the workflow builder (similar complexity to Make) and the self-hosting setup (Docker, server configuration, SSL certificates). If you use n8n Cloud, the setup time drops to match Make's. The workflow builder itself is intuitive for anyone with technical background—the node-based visual editor is logical and well-documented. For developers, n8n feels natural almost immediately. For non-technical users, it is a steeper climb. n8n documentation and the n8n community forum are the primary learning resources.

The complete side-by-side comparison table

| Feature | Zapier | Make | n8n | |---|---|---|---| | App library | 7,000+ | 1,800+ | 400+ (+ custom nodes) | | Pricing model | Per task | Per operation | Flat (self-hosted) or per execution (cloud) | | Free tier | 100 tasks/mo | 1,000 ops/mo | Unlimited (self-hosted) | | Starting paid price | $29.99/mo | $10.59/mo | $24/mo (cloud) or $5–10/mo (VPS) | | Cost at 50K executions/mo | $250+ | $50–70 | $10–20 (server) | | Learning curve | Low (1–2 hrs) | Medium (3–5 hrs) | Medium-High (5–10 hrs) | | Complex branching | Basic (3 paths) | Advanced (unlimited) | Advanced (unlimited) | | Error handling | Notifications only | Route-level handlers | Workflow + node-level handlers | | Self-hosting | No | No | Yes (open-source) | | EU data centres | No (US only) | Yes (Frankfurt) | Your choice (self-hosted) | | Data sovereignty | Low | Medium | Full | | AI/LLM integration | Strong (native + AI by Zapier) | Strong (native modules) | Very strong (AI agents, LangChain, local LLMs) | | Data stores | Zapier Tables | Built-in data stores | Any database (self-managed) | | Multi-user/teams | Team plan ($103.50/mo) | Teams plan ($34.12/mo) | Unlimited users (self-hosted) | | API/webhook support | Yes | Yes (deeper) | Yes (most flexible) | | Custom code | Limited (Code by Zapier) | JavaScript module | Full JS/Python Code nodes | | Best for | Non-technical, simple flows | Complex flows, mid-market | Developers, agencies, data-sensitive |

Decision matrix: which tool for your situation

Choose Zapier if:

• You are non-technical and need to start automating today
• Your workflows are straightforward (2–5 steps, one trigger, linear actions)
• The apps you use are all in Zapier's 7,000+ library, especially niche or industry-specific tools
• Speed-to-value matters more than long-term cost
• You have a small budget and low volume (under 750 tasks/month fits the base plan)
• You want the largest community, most templates, and best documentation

Choose Make if:

• You have medium-to-complex workflows (conditional logic, multiple branches, array processing)
• Cost efficiency matters—you process 5,000+ operations/month and want to spend less than Zapier
• You need strong error handling for production workflows
• EU data residency is a requirement (GDPR compliance)
• You have outgrown Zapier's capabilities but do not want to self-host
• You appreciate visual workflow building and want to see your entire process as a flowchart
• Your team includes semi-technical users who can invest 3–5 hours in learning

Choose n8n if:

• You have a developer or technical team member who can manage self-hosting
• Data sovereignty is non-negotiable (healthcare, finance, government, EU data residency)
• You process high volume (10,000+ executions/month) and want predictable, low infrastructure costs
• You are an agency serving multiple clients and need fixed-cost infrastructure with per-client isolation
• You want to build AI agent workflows with LangChain, local LLMs, or RAG pipelines
• You need custom integrations that no platform covers natively (the Code node handles anything)
• Open-source values matter to your organisation

Still undecided?

Start with Make. It offers the best balance: more powerful than Zapier, more accessible than n8n, and priced competitively. If you later need self-hosting or unlimited executions, migrating from Make to n8n is conceptually straightforward (both use visual, node-based builders). Going the other direction—from Zapier to Make or n8n—often requires rebuilding workflows from scratch because the paradigms differ.

Combining platforms: the hybrid approach

Many mature automation practices use more than one platform. A common pattern:

• Zapier for quick internal tools and one-off integrations where a niche app connector is only available on Zapier
• Make for client-facing or revenue-critical workflows that need robust error handling
• n8n self-hosted for high-volume data processing, AI workflows, or anything touching sensitive data

This is not wasteful duplication—it is pragmatic. Each tool has a sweet spot. Using the right tool for each job category reduces cost and increases reliability across your automation portfolio.

Migration considerations

Moving from Zapier to Make

Make provides a migration guide and an import tool for basic Zaps. Complex Zaps will need manual rebuilding. Plan for 1–3 hours per workflow for straightforward migrations, longer for complex multi-path Zaps. The biggest adjustment is mental: Make's scenario model is more expressive, and you will likely want to restructure workflows to take advantage of features (routers, error handlers) that Zapier lacked.

Moving from Zapier or Make to n8n

No automated migration tool exists. Each workflow must be recreated in n8n's builder. The concepts map closely (triggers → trigger nodes, actions → action nodes, filters → IF nodes), but connectors differ. Budget 2–5 hours per workflow. The n8n migration guide and community forum provide patterns for common migrations.

Vendor lock-in risk

Zapier has the highest lock-in due to its proprietary format and largest connector ecosystem (some apps are only on Zapier). Make has moderate lock-in—workflows are scenario-based and exportable, but connectors are platform-specific. n8n has the lowest lock-in: workflows are JSON files, the platform is open-source, and custom nodes are npm packages you control.

Real-world performance and reliability

All three platforms maintain high uptime. Zapier publishes a status page with historical uptime consistently above 99.9%. Make's status page shows comparable reliability. n8n's reliability depends on your hosting infrastructure for self-hosted instances; n8n Cloud provides managed uptime guarantees.

Execution speed varies. Zapier webhooks typically trigger within 1–2 seconds. Make scenarios execute near-instantly for webhook triggers. n8n self-hosted performance depends on your server specifications but is generally fast with adequate resources (2GB RAM minimum recommended for production workloads).

When to bring in an expert

If you have evaluated these tools and are still unsure, or if you have tried one and hit a wall—missing connector, complex conditional logic, error handling requirements, multi-system architectures, or regulatory compliance needs—an automation expert can save you weeks of trial and error. Experienced specialists know which tool fits your specific tech stack and business requirements. They have built hundreds of workflows and can identify pitfalls before you hit them.

For a broader framework on when to build yourself vs. hire help, see when to hire an automation expert. For a guide to what no-code automation can and cannot do, read no-code automation explained. And if you want to understand the financial case for automation, our automation ROI guide provides the framework.

Browse Zapier, Make, and n8n experts on LogicLot, or post a Custom Project describing your tech stack, volume, and requirements.