Databricks architecture overview

This article provides a high-level overview of Databricks architecture, including its enterprise architecture, in combination with AWS.

High-level architecture

Databricks operates out of a control plane and a compute plane.

  • The control plane includes the backend services that Databricks manages in your Databricks account. The web application is in the control plane.

  • The compute plane is where your data is processed. There are two types of compute planes depending on the compute that you are using.

    • For serverless compute, the serverless compute resources run in a serverless compute plane in your Databricks account.

    • For classic Databricks compute, the compute resources are in your AWS account in what is called the classic compute plane. This refers to the network in your AWS account and its resources.

Each Databricks workspace has an associated storage bucket known as the workspace storage bucket. The workspace storage bucket is in your AWS account.

The following diagram describes the overall Databricks architecture.

Diagram: Databricks architecture

Serverless compute plane

In the serverless compute plane, Databricks compute resources run in a compute layer within your Databricks account. Databricks creates a serverless compute plane in the same AWS region as your workspace’s classic compute plane.

To protect customer data within the serverless compute plane, serverless compute runs within a network boundary for the workspace, with various layers of security to isolate different Databricks customer workspaces and additional network controls between clusters of the same customer.

To learn more about networking in the serverless compute plane, Serverless compute plane networking.

Classic compute plane

In the classic compute plane, Databricks compute resources run in your AWS account. New compute resources are created within each workspace’s virtual network in the customer’s AWS account.

A classic compute plane has natural isolation because it runs in each customer’s own AWS account. To learn more about networking in the classic compute plane, see Classic compute plane networking.

For regional support, see Databricks clouds and regions.

Workspace storage bucket

When you create a workspace, you provide an S3 bucket and prefix to use as the workspace storage bucket.

The workspace storage bucket contains:

  • Workspace system data: Workspace system data is generated as you use various Databricks features such as creating notebooks. This bucket includes notebook revisions, job run details, command results, and Spark logs

  • DBFS: DBFS (Databricks File System) is a distributed file system in Databricks environments accessible under the dbfs:/ namespace. DBFS root and DBFS mounts are both in the dbfs:/ namespace. Storing and accessing data using DBFS root or DBFS mounts is a deprecated pattern and not recommended by Databricks. For more information, see What is DBFS?.

  • Unity Catalog workspace catalog: If your workspace was enabled for Unity Catalog automatically, the workspace storage bucket contains the default workspace catalog. All users in your workspace can create assets in the default schema in this catalog. See Set up and manage Unity Catalog.