Databricks on AWS is a popular deployment choice that offers flexibility and leverages the widely used AWS ecosystem. Here’s what you need to know:

Key Features of Databricks on AWS

• • Wide AWS Integration: Seamlessly connect to numerous AWS data services:S3: Use Amazon S3 as your primary data lake storage.
  • Redshift: Integrate with AWS Redshift for data warehousing.
  • DynamoDB, RDS, Kinesis, Glue: Connect to various database services, streaming sources, and AWS’s data catalog.
• Flexibility: While Databricks offers managed services on AWS, you have more control over infrastructure setup and configurations compared to Azure Databricks.
• AWS Ecosystem Advantage: Leverage the vast array of AWS tools and services for security (IAM), machine learning (SageMaker), networking, and more.
• Performance Optimization: Ability to fine-tune cluster configurations and leverage specific AWS instance types for optimized performance needs.

How Databricks Works on AWS

1. Databricks Control Plane: The core Databricks management service runs within Databricks’ cloud account.
2. Your AWS Account: You provision Databricks workspaces within your own AWS account. This gives you ownership of the compute resources (EC2 instances) and data stored within your AWS account.

Why Choose Databricks on AWS

• Customization: More control over the underlying infrastructure and configuration of your Databricks workspaces.
• Existing AWS Footprint: Ideal if your organization is already heavily invested in AWS and wants to consolidate data tools.
• Broad Integration:  The extensive range of AWS services provides great flexibility around your data stack.

Considerations

• Complexity: Compared to Azure Databricks, setup and management may potentially be slightly more complex due to less integrated configuration options.

Getting Started

1. AWS Account: You’ll need an active AWS account.
2. Databricks Account: Create a Databricks account, and then go through the Databricks workspace deployment process within your AWS console.