Trigger.dev vs Flowise

Detailed side-by-side comparison to help you choose the right tool

Trigger.dev

🔴Developer

Automation & Workflows

Open-source background job platform for AI agents providing long-running task execution, retries, and scheduling with serverless deployment.

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Starting Price

Free

Flowise

🟡Low Code

Automation & Workflows

Open-source no-code AI workflow builder and visual LLM application platform with drag-and-drop interface. Build chatbots, RAG systems, and AI agents using LangChain components, supporting OpenAI, Anthropic, vector databases, and custom integrations for creating sophisticated conversational AI systems.

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Starting Price

Free

Feature Comparison

Scroll horizontally to compare details.

FeatureTrigger.devFlowise
CategoryAutomation & WorkflowsAutomation & Workflows
Pricing Plans4 tiers4 tiers
Starting PriceFreeFree
Key Features
    • Workflow Runtime
    • Tool and API Connectivity
    • State and Context Handling

    Trigger.dev - Pros & Cons

    Pros

    • Solves long-running execution for agents
    • Excellent developer experience
    • Built-in retry and scheduling
    • Strong observability
    • Open-source self-hosted option

    Cons

    • TypeScript-focused (no Python SDK)
    • Free tier timeout may be limiting
    • Cloud pricing can add up at scale
    • Not agent-specific — general background job platform

    Flowise - Pros & Cons

    Pros

    • Visual builder backed by real LangChain/LlamaIndex code — full framework power without writing boilerplate
    • Comprehensive component library covering all major LLM providers, vector stores, and LangChain integrations
    • One-click API deployment with built-in chat widget for website embedding — fast path from prototype to deployment
    • Open-source and self-hostable with simple Node.js deployment via npm, Docker, or one-click cloud platforms
    • Active community marketplace with pre-built chatflows for common use cases (RAG, agents, customer support)

    Cons

    • Requires understanding LangChain/LlamaIndex concepts — the visual interface doesn't abstract away framework complexity
    • Complex workflows with many conditional branches become visually cluttered and hard to manage on the canvas
    • Debugging node connection issues can be frustrating — error messages from the underlying framework are passed through without simplification
    • Custom component development requires TypeScript knowledge and understanding of Flowise's component architecture

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    🔒 Security & Compliance Comparison

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    Security FeatureTrigger.devFlowise
    SOC2
    GDPR
    HIPAA
    SSO
    Self-Hosted✅ Yes
    On-Prem✅ Yes
    RBAC✅ Yes
    Audit Log
    Open Source✅ Yes
    API Key Auth✅ Yes
    Encryption at Rest
    Encryption in Transit✅ Yes
    Data Residency
    Data Retentionconfigurable
    🦞

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