Realtime overview

Get live run updates and stream data from background tasks to your frontend or backend. No polling.

Realtime is the umbrella for everything live in Trigger.dev. It covers two things: getting notified when a run’s state changes, and streaming continuous data (like AI tokens) from a running task to your app.

Both use the same @trigger.dev/react-hooks package and the same authentication system. The difference is what they give you.

Run updates vs Streaming

	Run updates	Streaming
What you get	Run state: status, metadata, tags	Continuous data you define (AI tokens, file chunks, progress)
When it fires	On state changes	While the task runs, as data is produced
Use case	Progress bars, status badges, dashboards	AI chat output, live logs, file processing
React hook	useRealtimeRun	useRealtimeStream
Setup in task code?	No, automatic	Yes, using streams.define()
Infrastructure	Electric SQL (PostgreSQL sync)	Streams transport

You can use both at the same time. Subscribe to a run’s status (to show a progress bar) while also streaming AI output (to display tokens as they arrive).

Run updates

Subscribe to a run and your code gets called whenever its status, metadata, or tags change. No setup needed in your task code.

You can subscribe to:

• Specific runs by run ID
• Runs with specific tags (e.g., all runs tagged with user:123)
• Batch runs within a specific batch
• Trigger + subscribe combos that trigger a task and immediately subscribe (frontend only)

→ React hooks | Backend

Streaming

Define typed streams in your task, pipe data to them, and read that data from your frontend or backend as it’s produced. You need to set up streams in your task code using streams.define().

→ How to emit streams from tasks | React hooks | Backend

Authentication

All Realtime hooks and functions require authentication. See the authentication guide for setup.

Frequently asked questions

How do I show a progress bar for a background task?

Use run metadata to store progress data (like a percentage), then subscribe to the run with useRealtimeRun. Your component re-renders on every metadata update.

How do I stream AI/LLM responses from a background task?

Define a stream in your task with streams.define(), pipe your AI SDK response to it, then consume it in React with useRealtimeStream. See Streaming data from tasks for the full guide.

Do I need WebSockets or polling?

No. Run updates are powered by Electric SQL (HTTP-based PostgreSQL syncing). Streams use their own transport. The hooks handle connections automatically.

Can I use both run updates and streaming together?

Yes. A common pattern: subscribe to run status with useRealtimeRun (progress indicator) while streaming AI output with useRealtimeStream (token-by-token display).