# Source: https://trigger.dev/docs/guides/use-cases/data-processing-etl.md

> ## Documentation Index
> Fetch the complete documentation index at: https://trigger.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Data processing & ETL workflows

> Learn how to use Trigger.dev for data processing and ETL (Extract, Transform, Load), including web scraping, database synchronization, batch enrichment and more.

## Overview

Build complex data pipelines that process large datasets without timeouts. Handle streaming analytics, batch enrichment, web scraping, database sync, and file processing with automatic retries and progress tracking.

## Featured examples

<CardGroup cols={3}>
  <Card title="Realtime CSV importer" icon="book" href="/guides/example-projects/realtime-csv-importer">
    Import CSV files with progress streamed live to frontend.
  </Card>

  <Card title="Web scraper with BrowserBase" icon="book" href="/guides/examples/scrape-hacker-news">
    Scrape websites using BrowserBase and Puppeteer.
  </Card>

  <Card title="Supabase database webhooks" icon="book" href="/guides/frameworks/supabase-edge-functions-database-webhooks">
    Trigger tasks from Supabase database webhooks.
  </Card>
</CardGroup>

## Benefits of using Trigger.dev for data processing & ETL workflows

**Process datasets for hours without timeouts:** Handle multi-hour transformations, large file processing, or complete database exports. No execution time limits.

**Parallel processing with built-in rate limiting:** Process thousands of records simultaneously while respecting API rate limits. Scale efficiently without overwhelming downstream services.

**Stream progress to your users in real-time:** Show row-by-row processing status updating live in your dashboard. Users see exactly where processing is and how long remains.

## Production use cases

<CardGroup cols={1}>
  <Card title="MagicSchool AI customer story" href="https://trigger.dev/customers/magicschool-ai-customer-story">
    Read how MagicSchool AI uses Trigger.dev to generate insights from millions of student interactions.
  </Card>

  <Card title="Comp AI customer story" href="https://trigger.dev/customers/comp-ai-customer-story">
    Read how Comp AI uses Trigger.dev to automate evidence collection at scale, powering their open source, AI-driven compliance platform.
  </Card>

  <Card title="Midday customer story" href="https://trigger.dev/customers/midday-customer-story">
    Read how Midday use Trigger.dev to sync large volumes of bank transactions in their financial management platform.
  </Card>
</CardGroup>

## Example workflow patterns

<Tabs>
  <Tab title="CSV file import">
    Simple CSV import pipeline. Receives file upload, parses CSV rows, validates data, imports to database with progress tracking.

    <div align="center">
      ```mermaid  theme={"theme":"css-variables"}
      graph TB
          A[importCSV] --> B[parseCSVFile]
          B --> C[validateRows]
          C --> D[bulkInsertToDB]
          D --> E[notifyCompletion]
      ```
    </div>
  </Tab>

  <Tab title="Multi-source ETL pipeline">
    **Coordinator pattern with parallel extraction**. Batch triggers parallel extraction from multiple sources (APIs, databases, S3), transforms and validates data, loads to data warehouse with monitoring.

    <div align="center">
      ```mermaid  theme={"theme":"css-variables"}
      graph TB
          A[runETLPipeline] --> B[coordinateExtraction]
          B --> C[batchTriggerAndWait]

          C --> D[extractFromAPI]
          C --> E[extractFromDatabase]
          C --> F[extractFromS3]

          D --> G[transformData]
          E --> G
          F --> G

          G --> H[validateData]
          H --> I[loadToWarehouse]
      ```
    </div>
  </Tab>

  <Tab title="Parallel web scraping">
    **Coordinator pattern with browser automation**. Launches headless browsers in parallel to scrape multiple pages, extracts structured data, cleans and normalizes content, stores in database.

    <div align="center">
      ```mermaid  theme={"theme":"css-variables"}
      graph TB
          A[scrapeSite] --> B[coordinateScraping]
          B --> C[batchTriggerAndWait]

          C --> D[scrapePage1]
          C --> E[scrapePage2]
          C --> F[scrapePageN]

          D --> G[cleanData]
          E --> G
          F --> G

          G --> H[normalizeData]
          H --> I[storeInDatabase]
      ```
    </div>
  </Tab>

  <Tab title="Batch data enrichment">
    **Coordinator pattern with rate limiting**. Fetches records needing enrichment, batch triggers parallel API calls with configurable concurrency to respect rate limits, validates enriched data, updates database.

    <div align="center">
      ```mermaid  theme={"theme":"css-variables"}
      graph TB
          A[enrichRecords] --> B[fetchRecordsToEnrich]
          B --> C[coordinateEnrichment]
          C --> D[batchTriggerAndWait]

          D --> E[enrichRecord1]
          D --> F[enrichRecord2]
          D --> G[enrichRecordN]

          E --> H[validateEnrichedData]
          F --> H
          G --> H

          H --> I[updateDatabase]
      ```
    </div>
  </Tab>
</Tabs>

## Featured use cases

<CardGroup cols={2}>
  <Card title="Data processing & ETL workflows" icon="database" href="/guides/use-cases/data-processing-etl">
    Build complex data pipelines that process large datasets without timeouts.
  </Card>

  <Card title="Media processing workflows" icon="film" href="/guides/use-cases/media-processing">
    Batch process videos, images, audio, and documents with no execution time limits.
  </Card>

  <Card title="AI media generation workflows" icon="wand-magic-sparkles" href="/guides/use-cases/media-generation">
    Generate images, videos, audio, documents and other media using AI models.
  </Card>

  <Card title="Marketing workflows" icon="bullhorn" href="/guides/use-cases/marketing">
    Build drip campaigns, create marketing content, and orchestrate multi-channel campaigns.
  </Card>
</CardGroup>