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

# Redshift

## Basic config

```yaml theme={"system"}
connector_type: redshift
profile: default            # profile in the io_config.yaml
config:
  table_name: table_name
  schema_name: schema_name  # Override the schema name. Default schema is "public"
```

## Alternative

Another option to stream data into Redshift is to stream data to Kinesis.
You can configure streaming ingestion for your Amazon Redshift cluster and create a materialized view using SQL statements.

You can follow [the guide from AWS](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion-getting-started.html) to set it up.

Or you can follow the steps below to set up the materialized view.

### 1. Create and attach IAM role to Redshift cluster

Create an IAM Role which has the policies `AmazonKinesisReadOnlyAccess` and `AmazonRedshiftFullAccess`.
Go to the Redshift cluster's `Properties` tab. In the `Cluster permissions` section, attach the IAM role to the Redshift cluster.

### 2. Create an external schema from Kinesis

Go to Redshift cluster's query editor, execute the command to create the schema:

```sql theme={"system"}
CREATE EXTERNAL SCHEMA redshift_stream_test
FROM KINESIS
IAM_ROLE <kinesis-redshift-iam-role-arn>;
```

### 3. Create a materialized view which loads data from Kinesis stream

Execute the command in query editor to create the materialized view from the kinesis stream:

```sql theme={"system"}
CREATE MATERIALIZED VIEW mage_kinesis_redshift_stream
AUTO REFRESH YES
AS
SELECT
    *,
    json_parse(kinesis_data) as payload
FROM redshift_stream_test."kinesis-stream-name"
```

You can change the materialized view name to the name you want to use.

### 4. Query data in the materialized view.

Execute the command to query the data:

```sql theme={"system"}
SELECT * FROM mage_kinesis_redshift_stream;
```