Modern teams expect their automation stack to do more than pass data between applications, they need reliability, granular control, strong data governance, and the ability to scale workflows as complexity grows. As organizations evaluate platforms like n8n, Zapier, and Make, the question is no longer simply “Which tool connects the most apps?” but rather which platform offers the deepest control over logic, data, architecture, and cost behavior. This guide provides a detailed, technical evaluation of all three platforms, comparing their hosting models, security tradeoffs, workflow expressiveness, developer extensibility, pricing mechanics, and operational maturity, so you can confidently choose the right foundation for your automation strategy.

n8n vs Zapier vs Make: (Pricing, Hosting, Limits)

Data Control & Compliance: Self-Hosting vs Cloud-Only

When organizations define “control,” they usually include data residency, governance, access boundaries, credential storage, and auditability. Under that definition, n8n offers the strongest control surface because teams can self-host within their own VPC. Credentials, logs, workflow data, and secrets can remain entirely internal.

Zapier is cloud-only; while SOC 2 and GDPR compliant, data always travels through Zapier systems.

Make is also cloud-only, but offers SOC 2 Type II and EU/US data residency choices, helping teams with location-bounded governance requirements.

An added governance factor: In 2025, Zapier disclosed unauthorized access to internal code repositories (not production systems). Security-sensitive teams may weigh this when selecting infrastructure.

Workflow Control: Branching, Iteration & Failure Management

Make offers the deepest visual control: Routers (parallel logic), Iterators (array processing), and module-level error handling with retry/ignore strategies.

n8n uses node-level fail-through plus global Error Workflows for centralized exception capture, escalation, or containment.

Zapier added enhanced error handling plus Auto-Replay, but each Zap has a 100-step maximum, so complex branching often requires chaining across multiple Zaps.

n8n vs Zapier vs Make: Technical Comparison for Developers & Low-Code Teams

This section highlights capabilities relevant to engineers, technical operators, and low-code builders evaluating these platforms from an extensibility and maintainability perspective.

Low-Code Flexibility & Learning Curve

Make

• Strongest operator-level visual abstraction
• Clean mapping, transformation, iteration, and aggregation
• Ideal for operations and product teams with minimal dev support

Zapier

• Simplest linear model
• Good for straightforward event → action workflows
• Limited expressiveness for complex data handling

n8n

• Best suited to teams comfortable with JSON, API schemas, and multi-branch logic
• A lower-level, systems-oriented approach with richer integration patterns

Code Execution & Custom Integration

n8n

• First-class JavaScript execution
• Custom modules, nodes, and packages are possible when self-hosted
• Works well as a programmable orchestrator

Zapier

• Zapier CLI enables custom apps
• JS execution is possible but sandboxed
• Good trade-off for teams building many lightweight connectors

Make

• Limited code execution; transformation is geared toward UI-driven mapping
• Excellent at JSON hydration and structured operations

API & Webhook Capabilities

• n8n is strongest for system-level API orchestration, including streaming, multi-service logic, and custom retry approaches.
• Make has powerful transformation operators for complex JSON payloads.
• Zapier provides a well-defined HTTP client suitable for transactional automation.

Environment, Deployment & Secrets Management

n8n provides full architectural control, including air-gapped deployments. Make and Zapier remain cloud-only.

Versioning, Portability & Release Management

n8n aligns well with GitOps models. Zapier supports versioning mostly for custom integrations rather than workflows. Make exports scenarios, but lacks deep versioning and deployment workflows.

Worker Scaling & Performance

n8n can be tuned to operate like a lightweight orchestration engine alongside queues and caches.
Make handles parallel branching efficiently and excels at high-volume API fan-out scenarios.
Zapier is strong for standard business event automations.

Best Platform by Technical Use Case

Architecture Patterns

n8n often operates as an internal orchestration service:

• webhook → worker → DB/service → notification
• event → queue → n8n → microservice chain

Make excels when processing JSON arrays, batching, or applying conditional branching via Routers and Iterators.

Zapier is most aligned with linear transactional workflows across commercial SaaS systems.

Architecture Patterns

The three platforms differ significantly in how they are most effectively used within modern automation architectures.

n8n
n8n is frequently adopted as an internal workflow orchestration layer, sitting between event sources and operational services. Teams often deploy it in their VPC and integrate it directly with internal systems, message brokers, and data stores.

Common patterns include:

• Webhook → n8n → DB/Service → Notification
  Example: Capture inbound events, persist them, or enrich them with internal systems before triggering business logic.
• Event → Queue → n8n → Microservice Chain
  Example: Receive events from Kafka/RabbitMQ/SQS and orchestrate multi-step processing across microservices.

n8n is particularly strong when workflows need to call internal APIs, perform custom logic, or integrate with private services.

Make
Make is most effective when processing structured datasets or multi-path logic within a single scenario. Routers, iterators, and aggregators allow it to handle arrays, collections, and batching with minimal workflow fragmentation. It excels in use cases where data must be transformed, filtered, or distributed across systems in parallel.

Zapier
Zapier is best aligned with SaaS → SaaS transactional automations, such as updating CRMs, sending notifications, or syncing records. It operates most efficiently as a straightforward trigger→action pipeline, without the need for deep branching or looping.

App Ecosystem Depth

Zapier
With more than 6,000 integrations, Zapier offers the broadest ecosystem, making it ideal for organizations that rely heavily on commercial SaaS platforms.

Make
Make supports 3,000+ applications, covering most popular cloud products. Its visual mapping and transformation tools often reduce the need for custom API work.

n8n
The n8n ecosystem continues to expand. While smaller than Zapier or Make, it compensates with strong HTTP Request and Code nodes, enabling quick integration with virtually any API even without an official connector. This flexibility makes it attractive for technical teams.

Limits That Influence Control

Zapier: 100-Step Cap per Zap
Each Zap is restricted to 100 steps, including branches and utility steps. This constraint encourages splitting logic across multiple Zaps, adding operational overhead and cost.

Make: No Hard Step Count
Make does not impose a traditional step limit. Complex workflows are handled within a single scenario, though total operations still consume credits. This flexibility is valuable for multi-path, iterative, or heavily branched processes.

n8n: No Practical Editor Limit
n8n imposes no functional limit on workflow size. The real boundary is execution volume or infrastructure capacity (cloud or self-host). This makes it suitable for large, nested logic without fragmentation.

Scalability & Reliability Considerations

Zapier
Webhook-driven workloads can experience queuing under volume spikes, though Zapier will process them when capacity allows. Run history, manual replays, and Auto-Replay features support operational continuity.

Make
Make offers granular module-level error handling, allowing workflows to continue even when individual branches fail. This localized failure tolerance makes Make resilient during partial API outages or data mismatches.

n8n
In cloud mode, scalability depends on execution quotas; in self-hosted deployments, reliability is determined by underlying infrastructure, compute, storage, database resilience, and redundancy. Hardening guidance exists for secure and highly available setups, enabling n8n to operate as a production-grade orchestration engine.

Pricing & Cost Predictability

Pricing determines how reliably you can forecast spend as your workflows scale. While all three platforms meter usage, the definition of a “unit” differs, impacting predictability for branching, iteration, and high-volume workloads.

Zapier: Task-Based

Zapier charges per task, meaning each successful step counts.
A 5-step workflow run 500 times consumes 2,500 tasks. Filters, formatters, and some utilities may count as tasks, while the 100-step cap often forces users to chain multiple Zaps, multiplying cost.
Predictability is strong for simple, linear automations, but branching or iterative logic can drive usage up quickly.

Make: Credit-Based

Make bills per operation (credit). Each module run consumes credits, and some modules cost more depending on data volume.
Its routers and iterators keep complex logic within a single scenario, making multi-path execution more cost-efficient than Zapier.
Costs remain predictable once you know how many operations each scenario triggers, especially for data-heavy or multi-branch workflows.

n8n: Execution-Based (Cloud) + Infrastructure (Self-Host)

n8n Cloud pricing is based on executions, not steps. One workflow run, regardless of how many nodes it touches, counts as a single unit.
Self-hosting shifts cost to compute + storage, which can be inexpensive at low or medium scale. This makes n8n especially cost-efficient for large, complex automations, though ops overhead must be considered for production environments.

Recommendations by Use Case

Migration Considerations

• Review pricing unit conversion and throughput requirements before cutover
• Zapier → Make: Replace Paths with Routers; plan per-module error handling
• Zapier / Make → n8n: Recreate logic, centralize errors, apply hardening

Conclusion

n8n, Zapier, and Make each solve automation challenges well, but they serve different levels of operational maturity. Zapier remains the most accessible option for teams that prioritize speed and broad SaaS coverage. Make delivers stronger visual workflow control and is better suited to multi-branch, iterative processes. n8n offers the deepest flexibility through self-hosting, custom logic, and integration with internal systems, making it ideal for engineering-led organizations that value data governance and extensibility.

Ultimately, the right choice depends on your architecture, compliance needs, and workflow complexity. Teams that want simplicity will favor Zapier, those building dynamic data flows will lean toward Make, and organizations needing full control and scalability will benefit most from n8n.

FAQs