> ## 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.

# Connections and credentials overview

Before you can run pipelines in Maia, you need a connection to your cloud data platform. This section covers platform-specific setup for Amazon Redshift and Databricks, and secure connectivity options for AWS-hosted resources.

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## Amazon Redshift

[Amazon Redshift](https://docs.maia.ai/docs/guides/amazon-redshift-connection.md) and [Amazon Redshift Serverless](https://docs.maia.ai/docs/guides/amazon-redshift-serverless-connection.md) are both supported as cloud data warehouses. Redshift Serverless is optimized for Full SaaS deployments, but works with Hybrid SaaS too.

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## Databricks

Maia connects to Databricks on both AWS and Azure, in Full SaaS and Hybrid SaaS deployments. You can connect your workspace using [Databricks Partner Connect](https://docs.maia.ai/docs/guides/databricks-partner-connect.md), and configure a [Databricks Jobs Compute cluster](https://docs.maia.ai/docs/guides/databricks-jobs-compute.md) to run and schedule transformation pipelines cost-effectively. For general setup, read the [Databricks connection guide](https://docs.maia.ai/docs/guides/databricks-cdw-guide.md).

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## Secure connectivity with AWS PrivateLink

[AWS PrivateLink](https://docs.maia.ai/docs/guides/aws-privatelink.md) lets you connect to an AWS VPC without exposing traffic to the public internet. Use it to secure connections to Snowflake, Amazon Redshift, or other AWS-hosted data sources. If you're running a Maia runner in your own AWS account under Hybrid SaaS, read [Connecting Maia runners via AWS PrivateLink](https://docs.maia.ai/docs/guides/connecting-via-privatelink.md) instead.


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