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

# Data Pipelines Overview

> Export Mixpanel data to external warehouses

# Data Pipelines API

The Data Pipelines API allows you to create continuous data pipelines that export your Mixpanel data to external warehouses like BigQuery, Snowflake, S3, and more.

## Base URL

```
https://data.mixpanel.com/api/2.0/nessie
```

## Authentication

Use Service Account or Project Secret with HTTP Basic Auth.

## Pipeline Types

### Raw Exports

Export raw JSON data to cloud storage:

* **Amazon S3**: Raw event data to S3 buckets
* **Google Cloud Storage**: Raw event data to GCS buckets
* **Azure Blob Storage**: Raw event data to Azure containers

### Schematized Exports

Export structured data to data warehouses:

* **BigQuery**: Schematized data to Google BigQuery
* **Snowflake**: Schematized data to Snowflake
* **AWS Glue**: Schematized data with AWS Glue catalog
* **Azure Synapse**: Schematized data to Azure

## Available Endpoints

### Pipelines Management

* **List Pipelines**: Get all pipelines for a project
* **Create Pipeline**: Set up a new data pipeline
* **Edit Pipeline**: Modify pipeline configuration
* **Delete Pipeline**: Remove a pipeline
* **Pause/Resume Pipeline**: Control pipeline execution

[View Pipeline Management \u2192](/api-reference/data-pipelines/schemas)

### Warehouse Connectors

* **List Imports**: Get all warehouse imports
* **Create Import**: Configure warehouse data imports
* **Update Import**: Modify import settings
* **Delete Import**: Remove an import

[View Warehouse Connectors \u2192](/api-reference/data-pipelines/warehouse-connectors)

## Common Parameters

<ParamField query="project_id" type="number" required>
  Your Mixpanel project ID
</ParamField>

<ParamField body="type" type="string" required>
  Pipeline type: `gcs-raw`, `s3-raw`, `azure-raw`, `bigquery`, `snowflake`, `aws`, `azure-blob`, `gcs-schema`
</ParamField>

<ParamField body="data_source" type="string">
  What to export: `events` or `people`

  Default: `events`
</ParamField>

<ParamField body="from_date" type="string" required>
  Start date in `YYYY-MM-DD` format
</ParamField>

<ParamField body="to_date" type="string">
  End date in `YYYY-MM-DD` format. Leave empty for continuous export.
</ParamField>

<ParamField body="frequency" type="string">
  Export frequency: `hourly` or `daily`

  Default: `daily`
</ParamField>

## Quick Start

<Steps>
  <Step title="Choose your destination">
    Decide where you want to export your data (BigQuery, S3, etc.)
  </Step>

  <Step title="Create a pipeline">
    Use the Create Pipeline endpoint with your destination credentials
  </Step>

  <Step title="Monitor status">
    Check pipeline status and sync history
  </Step>

  <Step title="Query your data">
    Access exported data in your warehouse
  </Step>
</Steps>

## Best Practices

<AccordionGroup>
  <Accordion title="Start with a trial pipeline">
    Use `trial: true` to test with 30 days of data before committing to a full pipeline.
  </Accordion>

  <Accordion title="Choose the right schema type">
    * **Monoschema**: All events in one table (easier to query)
    * **Multischema**: Each event type in its own table (better for large volumes)
  </Accordion>

  <Accordion title="Enable sync for data integrity">
    Set `sync: true` to automatically update exported data when changes occur in Mixpanel.
  </Accordion>

  <Accordion title="Use appropriate frequency">
    * **Hourly**: For real-time analytics needs
    * **Daily**: For most analytical use cases (more efficient)
  </Accordion>
</AccordionGroup>