Inngest vs Trigger.dev

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

Inngest

🔴Developer

AI Agents

Durable-execution platform for AI workflows and agents — write step-functions in TypeScript or Python, get retries, scheduling and observability for free.

Was this helpful?

Starting Price

Free

Trigger.dev

🔴Developer

AI workflow infrastructure

an open-source TypeScript platform for building and deploying long-running AI agents and workflows with retries, queues, observability, realtime updates, and elastic scaling.

Was this helpful?

Starting Price

Free

Feature Comparison

Scroll horizontally to compare details.

FeatureInngestTrigger.dev
CategoryAI AgentsAI workflow infrastructure
Pricing Plans8 tiers4 tiers
Starting PriceFreeFree
Key Features
  • Step-based function execution with automatic retries
  • Event-driven workflow triggering and orchestration
  • Local development server with production parity

    💡 Our Take

    Choose Inngest if you need enterprise scale (100K+ executions/sec), AgentKit for AI workflows, and multi-language SDK support across TypeScript, Python, Go, and Kotlin. Choose Trigger.dev if you're a TypeScript-only team that prefers its long-running task model with v3's checkpointing, and you want a slightly more opinionated developer experience focused on Next.js and edge deployments.

    Inngest - Pros & Cons

    Pros

    • Durable execution survives crashes and resumes mid-workflow
    • AgentKit framework purpose-built for multi-step AI agents
    • Generous free tier: 50k runs/month with full features
    • Beautiful dashboard with traces, logs, and replay
    • Works on Vercel, Cloudflare Workers, Lambda, and containers

    Cons

    • TypeScript-first — Python SDK is less mature
    • Step-function programming model has a learning curve
    • Self-hosted Inngest available but most teams use the cloud
    • Pricing jumps from $30 Basic to $150 Pro tier feel steep mid-stage

    Trigger.dev - Pros & Cons

    Pros

    • Clear fit for agent backends rather than generic AI experimentation
    • Public product pages describe concrete capabilities such as long-running tasks and AI agent workflows
    • Pricing evidence is present in the record, so buyers can estimate a pilot before a sales call
    • Pairs well with adjacent tools when a workflow needs backend, automation, research, or creative support

    Cons

    • AI output still needs human review, especially for production, legal, tax, or customer-facing work
    • Teams must validate data handling, retention, permissions, and export options before rollout
    • Best results require a narrow process and clear inputs; vague tasks will produce inconsistent value

    Not sure which to pick?

    🎯 Take our quiz →
    🦞

    New to AI tools?

    Read practical guides for choosing and using AI tools

    🔔

    Price Drop Alerts

    Get notified when AI tools lower their prices

    Tracking 2 tools

    We only email when prices actually change. No spam, ever.

    Get weekly AI agent tool insights

    Comparisons, new tool launches, and expert recommendations delivered to your inbox.

    No spam. Unsubscribe anytime.

    Ready to Choose?

    Read the full reviews to make an informed decision