Overview of Databricks Premium Platform Access

Estimated read: 4 min

This section walks through the path you’ll need if you’re preparing for Part 3’s migration content, or if you specifically want the classic-compute, your-own-AWS-account setup described in the earlier architecture lecture. If you’re staying on Free Edition for now, skip ahead to Working in Databricks Workspace and come back here later.

The shape of this section

Seven remaining lectures, in order:

1. Create an AWS account, if you don’t already have one.
2. Create an AWS IAM user to administer the setup (rather than using the AWS root account for day-to-day work).
3. Set up AWS cost monitoring before you spend anything real – a habit worth having before, not after, your first bill.
4. Subscribe to Databricks through the AWS Marketplace, creating your Databricks account contract.
5. Create a serverless workspace on that account.
6. Create a classic workspace on that account – and understand when you’d actually reach for each.
7. Delete and clean up everything, so you’re not paying for a workspace you built purely to learn from.

Why go through this instead of just using Free Edition

Free Edition, from the earlier lecture, gets you a real workspace with zero AWS involvement. What it deliberately doesn’t give you is the thing a paid, AWS-account-linked workspace does: direct control over the AWS account your data lives in – your own S3 buckets, your own IAM roles, your own VPC if you need one. That control is exactly what Part 3’s migration content assumes, because a real migration project always runs inside a customer’s own AWS account, not a shared free tier.

Key term: the AWS Marketplace path is a billing mechanism, not a different product – Databricks itself is identical whether you subscribe directly or through the Marketplace. What changes is that usage shows up on your AWS bill instead of a separate Databricks invoice. See Databricks pricing for the underlying pay-as-you-go and committed-use models this billing sits on top of.

Cost-saving cleanup, up front

Before you start: every hands-on step in this section is designed to be fully reversible. The last lecture, Delete and Cleanup Databricks Workspace, walks through tearing everything down. If you’re only doing this to learn the setup flow, budget five extra minutes at the end to run that cleanup rather than leaving a workspace (and its underlying AWS resources) running.

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