ERR_MEMORY_EXCEEDED on Make.com: Memory limit exceeded. Root cause: The workflow is attempting to process a dataset that exceeds the platform's per-execution memory limit. This typically occurs when loading large record sets into memory, processing high-resolution file attachments, or running complex nested loops without pagination. Step 1: Identify which module is consuming the memory. Open the failed scenario run in Make.com (Scenarios → History → click the errored run). The module that caused the memory error will be marked with a red error indicator. Hover over it to see the error details. Memory errors most commonly occur in: Iterator modules processing large arrays, HTTP modules downloading large files, JSON Parse modules handling large payloads, or Aggregator modules collecting thousands of bundles. Step 2: Reduce the payload size at the source. If the memory error is in an HTTP or API module, you are likely downloading more data than you need. Add query parameters to filter the response: use date ranges (e.g., modified_after=2024-01-01), field selectors (e.g., ?fields=id,name,email instead of returning all fields), and pagination (limit=100 per request). Most REST APIs support these parameters — check the API documentation for the specific app. Step 3: Replace Iterator + Aggregator patterns with pagination loops. A common memory-heavy pattern is: fetch all records → Iterator → process each one → Aggregator. If you have 10,000 records, the Aggregator holds all 10,000 in memory simultaneously. Replace this with a pagination loop: use a Repeater module to fetch one page at a time (100 records), process each page, then move to the next. The Repeater pattern processes records sequentially without accumulating them in memory. Step 4: For file processing, use URLs instead of file data. If your scenario downloads files (images, PDFs, CSVs) and passes them between modules, each file is held in memory. Instead of downloading the file content, pass only the file URL between modules and download it only in the final module that needs the actual bytes. For Google Drive files, use the file ID and download only when writing to the destination. Step 5: Split the scenario at the memory-intensive module. If you cannot reduce the data volume, split the scenario into two. Scenario 1 processes records up to the memory-intensive step and stores intermediate results in a Make.com Data Store or sends them via webhook. Scenario 2 picks up from the Data Store and completes the processing. Each scenario runs with a fresh memory allocation, effectively doubling your available memory. Step 6: Upgrade your Make.com plan for higher memory limits. Make.com's memory limits increase with plan tier. If your use case genuinely requires processing large datasets in a single execution, upgrading to Pro or Teams provides higher limits. Contact Make.com support to ask for the exact memory limits per plan before upgrading — they are not published in the pricing page.