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

# Amazon Redshift connection

export const m_runner = "Maia runner";

export const maia = "Maia";

This page covers key resources you'll need to connect your Amazon Redshift instance to {maia}. You must configure this connection before running any data pipelines.

***

## Full SaaS or Hybrid SaaS?

{maia} supports both [Full SaaS and Hybrid SaaS deployment architectures](/docs/guides/architecture-overview).

* Amazon Redshift on AWS is compatible with both deployment types.
* Amazon Redshift Serverless is optimized for Full SaaS environments, but can also be used in Hybrid SaaS. Read [Amazon Redshift serverless](/docs/guides/amazon-redshift-serverless-connection) for details.

***

## Authentication

{maia} connects to Amazon Redshift using **username/password** authentication.

Use standard Amazon Redshift database credentials to authenticate. This method is required for environment configuration and related components. Ensure the Amazon Redshift cluster is configured with appropriate user access policies.

<Note>
  IAM roles and cloud credentials are used strictly for infrastructure access—such as {m_runner} execution roles, Amazon S3 staging, and secret retrieval. They are **not** used as a direct database authentication mechanism for Amazon Redshift connections.
</Note>

### Connection security

Connections between {maia} and Amazon Redshift can be secured using **SSL encryption**. Refer to the [Redshift SSL configuration](https://docs.aws.amazon.com/redshift/latest/mgmt/connecting-ssl-support.html) documentation for details.

***

## Compute types

The following Amazon Redshift compute options are supported:

* **Provisioned clusters:** Manually configured clusters for predictable workloads.
* **Amazon Redshift serverless (recommended):** Automatically scales based on workload demand.
* **RA3 instances:** Support managed storage with high performance. Read [Amazon Redshift instance types](https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-clusters.html) to learn more.

***

## Feature support and considerations

{maia} supports key Amazon Redshift features to enhance data workflows:

* **External tables via Amazon Redshift spectrum:** Query external data stored in Amazon S3.
* **Stored procedures and functions:** Build modular SQL-based transformations.
* **Materialized views:** Improve performance with pre-computed queries.
* **Workload management (WLM):** Prioritize workloads with query queues.
* **Federated queries:** Access data across other AWS services (e.g., RDS, Aurora).

***

## Role privileges and access management

Amazon Redshift uses a role-based access control (RBAC) model. Assign roles to control user access and responsibilities:

| Role                 | Responsibilities                                               |
| -------------------- | -------------------------------------------------------------- |
| Superuser            | Full administrative access to Amazon Redshift.                 |
| DBA role             | Manage database objects, permissions, and monitoring.          |
| ETL role             | Execute data transformations and load operations.              |
| Read-only            | Query access without modification privileges.                  |
| External Schema role | Access Amazon Redshift Spectrum and AWS Glue external schemas. |

### Best practices for managing Amazon Redshift roles

* Grant least privilege access.
* Enable RBAC to segment responsibilities.
* Regularly audit roles and logs.

Read more at [Amazon Redshift role-based access control](https://docs.aws.amazon.com/redshift/latest/dg/t_Roles.html)