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n8n Out of Memory (JavaScript Heap Out of Memory)

Workaround available n8n Cloud, self-hosted Updated October 21, 2026

Quick answer

n8n crashes with 'Execution stopped at this node (n8n may have run out of memory)' when a workflow loads too much data at once. Process items in batches, move heavy work into sub-workflows, and on self-hosted instances raise the Node.js heap limit.

Most likely fix: Process data in smaller batches.

Symptoms

Editor shows 'Execution stopped at this node (n8n may have run out of memory while executing it)', 'Problem running workflow', 'Connection Lost' or 503; self-hosted logs show 'Allocation failed - JavaScript heap out of memory'; the instance restarts.

Why it happens

  • Large JSON datasets or binary files held in memory
  • Memory-heavy Code or legacy Function nodes
  • Manual executions, which keep an extra copy of data for the editor
  • Many nodes or other workflows running concurrently
  • Node.js heap limit lower than available RAM

How to fix it

Try these in order — the most common fix is first.

  1. 1. Process data in smaller batches

    1. Add a Loop Over Items (formerly Split in Batches) node before heavy steps
    2. Set a batch size such as 200 instead of processing thousands of items at once

  2. 2. Move heavy processing into a sub-workflow

    1. Create a sub-workflow that does the heavy processing
    2. Call it with the Execute Workflow node
    3. Return only a small result to the parent so memory is freed after each batch

  3. 3. Raise the Node.js heap limit (self-hosted)

    1. Set NODE_OPTIONS=--max-old-space-size=4096 (choose a value that fits your host RAM)
    2. Restart the container
    3. Make sure no wrapper start script overrides NODE_OPTIONS

  4. 4. Store binary data on disk, not in memory

    1. Set N8N_DEFAULT_BINARY_DATA_MODE=filesystem (or s3)
    2. In-memory binary mode was removed in n8n 2.0

  5. 5. Avoid manual runs and Code nodes for big data

    1. Test with a small sample, then run large jobs via the active workflow
    2. Replace Code nodes with built-in nodes where possible
    3. On n8n Cloud, upgrade to a larger plan for more memory

This guide also covers

  • n8n out of memory
  • n8n javascript heap out of memory
  • n8n may have run out of memory
  • n8n execution stopped at this node

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