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

# Redshift

> This page outlines how to use the Redshift integration to create and manage your data warehouse in Cargo.

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze data using standard SQL. Cargo's native integration with Redshift allows you to use it as your system of record—powering data models, plays, and automated workflows.

## How to set up Redshift

### Prerequisites

Before connecting Redshift to Cargo, ensure you have:

* An active Amazon Redshift cluster
* Network connectivity between Cargo and your Redshift cluster
* A dedicated schema and user for Cargo
* Proper IAM permissions and database credentials

### Connection details

To set up the connection, provide the following details when creating the connector:

| Field        | Description                                                               |
| ------------ | ------------------------------------------------------------------------- |
| **Host**     | Your Redshift endpoint (e.g., `cluster-id.region.redshift.amazonaws.com`) |
| **Port**     | Default is `5439`                                                         |
| **Database** | Your database name                                                        |
| **Username** | The Cargo service user (e.g., `cargo_user`)                               |
| **Password** | The user's password                                                       |

<Tip>
  Find your Redshift endpoint in the AWS Console under **Redshift → Clusters →
  Your Cluster → General information**.
</Tip>

***

## Redshift actions

Once connected, you can use Redshift in your workflows with the following actions:

### Insert

Insert new records into a Redshift table.

**Configuration**

| Field        | Description                                     |
| ------------ | ----------------------------------------------- |
| **Schema**   | The Redshift schema containing the target table |
| **Table**    | The table to insert data into                   |
| **Mappings** | Map columns to values using expressions         |

**Use cases**

* **Lead capture** – Insert new leads from form submissions or enrichment workflows
* **Event logging** – Record workflow events and outcomes
* **Data aggregation** – Store computed results for reporting

### Update

Update existing records in a Redshift table based on a matching column.

**Configuration**

| Field               | Description                                     |
| ------------------- | ----------------------------------------------- |
| **Schema**          | The Redshift schema containing the target table |
| **Table**           | The table to update                             |
| **Matching Column** | The column to match records against             |
| **Matching Value**  | The value to match (supports expressions)       |
| **Mappings**        | Map columns to new values using expressions     |

**Use cases**

* **Data enrichment** – Update records with enriched data from external sources
* **Status updates** – Mark records as processed or update stages
* **Sync external changes** – Keep Redshift in sync with CRM or other systems

### Upsert

Create new records or update existing ones based on a matching column.

**Configuration**

| Field               | Description                                     |
| ------------------- | ----------------------------------------------- |
| **Schema**          | The Redshift schema containing the target table |
| **Table**           | The table to upsert into                        |
| **Matching Column** | The column to match records against             |
| **Matching Value**  | The value to match (supports expressions)       |
| **Mappings**        | Map columns to values using expressions         |

**Use cases**

* **Data sync** – Keep your warehouse updated regardless of whether records exist
* **Idempotent operations** – Safely retry operations without creating duplicates
* **Master data management** – Maintain a single source of truth

### Delete

Delete records from a Redshift table based on a matching column.

**Configuration**

| Field               | Description                                     |
| ------------------- | ----------------------------------------------- |
| **Schema**          | The Redshift schema containing the target table |
| **Table**           | The table to delete from                        |
| **Matching Column** | The column to match records against             |
| **Matching Value**  | The value to match (supports expressions)       |

**Use cases**

* **Data cleanup** – Remove outdated or invalid records
* **GDPR compliance** – Delete personal data on request
* **Workflow automation** – Remove processed records from staging tables

***

## Redshift data models

Cargo allows you to create data models on top of your Redshift data that can be used to trigger Plays and power workflows.

### Creating Redshift data models

To create a Redshift data model:

1. Navigate to **Data Models** in Cargo
2. Click **Create data model**
3. Select **Redshift** as the source
4. Configure the following fields:

| Field             | Description                                                 |
| ----------------- | ----------------------------------------------------------- |
| **Name**          | Choose a descriptive name for your model                    |
| **Slug**          | Set a unique identifier that cannot be changed once created |
| **Schema**        | Select the Redshift schema containing your data             |
| **Table**         | Select the table or view to model                           |
| **ID Column**     | The column containing unique record identifiers             |
| **Title Column**  | The column to display as the record title                   |
| **Cursor Column** | (Optional) Column for incremental syncing (date or number)  |

### Using Redshift data models

Once created, your Redshift data model can be used to:

* **Trigger Plays** – Start automated workflows when data changes
* **Power enrichment** – Use Redshift data to enrich records in workflows
* **Create segments** – Filter and target specific records from your data

***

## Network configuration

If you restrict access to your Redshift cluster, add these Cargo IP addresses to your security group or VPC whitelist:

* `3.251.34.134`
* `54.220.135.99`
* `79.125.105.52`

**Update via AWS CLI**

```bash theme={null}
aws ec2 authorize-security-group-ingress \
    --group-id sg-your-security-group-id \
    --protocol tcp \
    --port 5439 \
    --cidr 3.251.34.134/32
```

***

## Security

* All Redshift connections are encrypted using SSL/TLS
* Credentials are securely stored and encrypted at rest
* Cargo uses dedicated user credentials with minimal required permissions
* Cargo never overwrites existing tables—it always creates its own