ActionApifyUpdated May 2026

How do I fetch results from an Apify run?

Short answer: Drop the "Apify → Get Dataset Items" action anywhere in your workflow, map the inputs from upstream nodes, and publish.

Use this action All 4 Apify actions

Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

Field	Type	Required	Description
Dataset ID datasetId	string	Required	Dataset ID
Limit limit	number	Optional	Limit

Sample request

{
  "datasetId": "{{trigger.datasetId}}",
  "limit": "{{trigger.limit}}"
}

Returns

[
  {
    "url": "https://example.com",
    "text": "Page content...",
    "title": "Example Page"
  }
]

Use these fields in downstream nodes for routing, logging, or error handling.

Triggered by

Apps that pair well as the trigger for Get Dataset Items.

Any of these apps can fire this action as part of a workflow.

Google Sheets → Apify

2 Google Sheets triggers

HubSpot → Apify

18 HubSpot triggers

FAQ

Questions about Get Dataset Items.

What does the Get Dataset Items action do in Apify?

Returns the records the actor wrote to its dataset (typically one record per scraped item — product, profile, search result). Shape depends entirely on the actor; check the actor's README in Apify Store for the schema before parsing downstream.

What inputs does Get Dataset Items require?

Required: Dataset ID. Every input accepts a static value or a variable from any upstream node in your workflow.

Can I use dynamic inputs from earlier workflow nodes?

Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.

What happens if Apify returns an error?

The workflow pauses on the failed node, the error message is captured in the run log, and you can retry the run with one click. Auto-retry policies are configurable per workflow with exponential backoff up to 5 attempts.

Does Get Dataset Items support batch operations?

Yes. Run Get Dataset Items inside a Loop node to process arrays. Tiny Command handles Apify's rate limits automatically so you don't have to throttle manually.

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