n8n vs Conduit: Automation or Data Streaming?

n8n and Conduit both move data between systems, but they solve very different problems. Picking the wrong one means rebuilding your pipeline later.

If you are comparing these two, you are likely deciding between real-time data streaming and event-driven business automation. This guide explains where each tool fits.

Key Takeaways

• Conduit is a data streaming platform: It moves data continuously between systems in real time, similar to how Kafka Connect works.
• n8n is a workflow automation platform: It automates business processes by connecting apps and triggering actions based on events.
• Conduit is not a workflow tool: It streams records between systems, but it does not route leads, send notifications, or run conditional business logic.
• n8n is not a data streaming tool: It handles event-driven automation well, but it is not built for high-throughput real-time data pipelines.
• Most teams use one or the other: They rarely compete for the same job in a production stack.

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Comparison Table

What Is Conduit and Who Uses It?

Conduit is an open-source data streaming platform built in Go. It moves data continuously between sources and destinations, similar to Kafka Connect but lighter to operate.

Data engineers use Conduit to build real-time pipelines that stream records from databases, queues, and APIs into other systems without batch delays.

• Connector-based architecture: Conduit uses source and destination connectors to define what data moves and where it goes.
• Real-time streaming: Data flows continuously as records change, not on a batch schedule. Latency stays low by design.
• Built in Go: The platform is lightweight and fast. Operators can write custom connectors in Go or use the built-in connector SDK.
• Kafka alternative: Conduit offers a simpler operational model for teams that want streaming without the overhead of managing a full Kafka cluster.
• Pipeline configuration: Pipelines are defined via YAML or the CLI, making them version-controllable and repeatable across environments.
• Open-source and self-hosted: Conduit runs on your own infrastructure with no vendor lock-in and no licensing fees.

Conduit is a strong fit for platform and data engineering teams that need reliable, low-latency data movement without the complexity of heavier streaming systems.

What Is n8n and Who Uses It?

n8n is an open-source workflow automation platform with a visual node editor. Business and operations teams use it to automate processes without writing code.

For a full picture of the platform, it is worth understanding what n8n is designed to do and the types of teams it is built for before comparing it to a data streaming tool like Conduit.

• Visual node editor: Connect triggers and actions by dragging nodes onto a canvas. No code required for most workflows.
• 400+ integrations: Native nodes for CRMs, project management tools, databases, communication platforms, and SaaS apps.
• Webhook triggers: React instantly to events from any app that can send an HTTP request to n8n.
• Custom code nodes: Add JavaScript or Python logic when built-in nodes do not cover your exact requirement.
• AI-native nodes: Built-in LLM integrations for classification, summarization, and AI-powered agent workflows.
• Self-hosted or cloud: Run on your own infrastructure for near-zero cost, or use n8n's managed cloud offering.

n8n is used by operations teams, RevOps professionals, marketing teams, and developers automating the connective tissue between business applications.

What Is the Core Technical Difference?

The difference comes down to what kind of data movement each tool is designed for. They approach the problem from opposite angles.

Conduit is built for continuous, high-throughput streaming between systems. n8n is built for event-driven automation that triggers business actions.

• Conduit is stream-oriented: It moves records continuously as they change, with low latency and no batch windows.
• n8n is event-oriented: It responds to triggers and executes workflow steps, including API calls, conditional logic, and notifications.
• Conduit is data-transport-focused: The platform cares about moving records reliably from source to destination with minimal transformation.
• n8n is action-focused: It is optimized for calling APIs, updating CRM records, sending messages, and routing data between business tools.
• Conduit targets platform engineers: Configuration is code-driven and assumes familiarity with infrastructure and pipeline operations.
• n8n targets operations teams: The visual editor and pre-built nodes make it accessible to non-developers building business workflows.

These differences mean the two tools rarely compete. Each solves a distinct class of problem in a modern data and automation stack.

What Use Cases Belong to Each Tool?

Choosing the right tool depends on whether your problem is a data engineering problem or a business operations problem.

A closer look at what n8n actually ships with at the platform level, not just the node count covers the range of automation scenarios it handles, from simple API calls to complex multi-step business workflows.

• Conduit for database replication: Stream changes from a Postgres production database to a downstream system in real time without batch lag.
• Conduit for event streaming: Move records from a message queue or CDC source to a data warehouse or another service continuously.
• Conduit for platform integration: Replace heavy Kafka Connect setups with a lighter, self-hosted streaming layer your team can operate easily.
• n8n for CRM automation: A new inbound lead triggers a HubSpot update, a Slack notification, and an onboarding email in one workflow.
• n8n for lead routing: Form submissions get enriched, scored, and routed to the right sales rep automatically without manual handling.
• n8n for AI document processing: Inbound emails trigger LLM-based extraction, classification, and CRM logging without human intervention.

If the goal is streaming data between systems continuously, use Conduit. If the goal is automating business actions triggered by events, use n8n.

Who Should Use Conduit?

Conduit has a well-defined audience. Outside that audience, it adds operational complexity that other tools handle more cleanly.

• Data engineers building streaming pipelines: Teams that need real-time data movement between services without running a full Kafka cluster.
• Platform teams replacing Kafka Connect: Engineering teams looking for a lighter self-hosted streaming solution with a simpler operational model.
• Teams with low-latency requirements: Situations where batch sync is too slow and data needs to reach its destination within seconds.
• Go-focused engineering teams: Organizations that prefer Go-based tooling and want to write custom connectors in a familiar language.

If your primary problem is moving data continuously between systems with low latency, Conduit belongs in your stack.

Who Should Use n8n?

n8n is the right tool for teams automating business operations. You do not need data engineering expertise to get value from it.

• Operations and RevOps teams: Automate lead routing, CRM updates, billing workflows, and customer onboarding without depending on engineering.
• Marketing teams: Connect ad platforms, email tools, and CRMs through automated workflows that respond to real-time events.
• Developers building internal tools: When the goal is connecting apps and triggering actions rather than streaming database records, n8n is the better fit.
• Teams building AI workflows: Native LLM nodes make n8n strong for enrichment, classification, and agent-based automation patterns.

Looking at how n8n workflows are structured and what makes them reliable in production shows what operational automation looks like across common business use cases.

How Does Deployment and Self-Hosting Compare?

Both tools are open-source and built for self-hosting. The deployment experience and operational overhead differ between them.

Understanding what the real trade-offs are between self-hosting n8n and using n8n Cloud walks through what each model requires in terms of maintenance, infrastructure, and ongoing operational effort.

• n8n Docker deployment: A simple Docker Compose setup gets you to production quickly. Documentation is thorough and community-maintained.
• n8n cloud: Fully managed, scales automatically, and requires zero infrastructure management from your team.
• Conduit self-hosted: Runs as a single binary or via Docker. Lightweight to operate compared to Kafka-based alternatives.
• Conduit configuration: Pipelines are defined in YAML files. Engineers familiar with CLI-based tooling will feel at home quickly.
• n8n resource requirements: Lightweight for most business automation workloads. A small VPS handles the majority of operational use cases.
• Conduit resource requirements: Scales with the volume of data being streamed and the number of active pipeline connectors.

For non-engineering teams, n8n's visual interface and managed cloud option make it the faster path to production. Conduit requires more hands-on infrastructure work.

How Do Pricing and Costs Compare?

Both tools are free to self-host. The total cost depends on infrastructure, managed hosting, and the time your team spends operating the platform.

• n8n self-hosted: Free software. Infrastructure costs typically run $10 to $50 per month for small to mid-sized deployments.
• n8n cloud: Managed hosting starts around $20 per month and scales with execution volume using transparent tier pricing.
• n8n enterprise: Custom pricing for organizations that need SSO, audit logging, and dedicated support at scale.
• Conduit self-hosted: Free and open-source. Infrastructure costs depend on the volume of data being streamed and the hosting environment.
• Conduit no managed cloud: At the time of writing, Conduit does not offer a hosted cloud tier, so self-hosting is the primary deployment path.
• Total cost comparison: n8n has predictable, modest costs for operational automation. Conduit costs scale with data engineering infrastructure requirements.

For operations teams, n8n's cost structure is simple and transparent. Conduit requires infrastructure investment that is appropriate for data engineering workloads.

Which Tool Should You Choose?

Once you understand whether your problem is data streaming or business process automation, the choice becomes straightforward.

• Choose Conduit when: You need real-time, continuous data movement between systems with low latency and a lightweight operational footprint.
• Choose n8n when: You need to automate business processes, connect SaaS tools, and trigger actions across your operations stack.
• Use both when: Your organization has a platform team streaming data between systems and an operations team automating business logic on top of it.

If you are still evaluating your options, it is worth reviewing what the real differences are between n8n and the tools teams most often compare it against, which covers the full landscape of automation and data pipeline tools across both categories.

Conclusion

n8n and Conduit solve fundamentally different problems. Conduit moves data between systems continuously in real time. n8n automates what your business does in response to events.

They rarely compete for the same job. In organizations that need both, they can coexist cleanly without overlap.

Choose the tool that matches the problem you are actually solving today.

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