Here is Post 2: Cloud Setup for Databricks (Azure & AWS) — written in a tutorial/blog format. It’s detailed, comparative, fact-based, interactive, and use-case-driven. Ideal for your Databricks Beginner → Advanced Series.

🚀 Post 2: Cloud Setup for Databricks (Azure & AWS) — A Comparative Guide for Data Engineers

Welcome to the second post in our Databricks Tutorial Series. In this guide, we’ll focus on how to set up and compare Databricks on Azure vs AWS—with real use cases, interactive elements, and best practices for each cloud.

🎯 What You’ll Learn

Key architectural differences: Azure vs AWS Databricks
Step-by-step setup for both platforms
Storage, security, cluster setup walkthrough
Use case-based examples (S3 vs ADLS, IAM vs AAD)
When to choose which cloud for Databricks

🧠 Why Does Cloud Setup Matter?

Databricks runs on top of cloud infrastructure, but how you:

store data (S3 vs ADLS)
secure data (IAM vs Azure AD)
connect notebooks, jobs, and clusters
…differs across AWS and Azure. Choosing the right setup influences cost, security, speed, and scale.

⚔️ Azure vs AWS Databricks — At a Glance

Feature	✅ Azure Databricks	✅ AWS Databricks
Native Cloud Storage	ADLS Gen2	Amazon S3
Identity & Access	Azure Active Directory (AAD)	IAM Roles / Policies
Managed Services	Azure-managed resource group & workspace	More manual setup, VPCs, S3, IAM
Marketplace Access	Azure Marketplace	AWS Marketplace
Networking	VNet, NSG, Private Link	VPC, Subnets, PrivateLink
Unity Catalog Support	✅ Yes (AAD-backed)	✅ Yes (IAM-backed)
Orchestration	Azure Data Factory / Logic Apps	Airflow, Step Functions, MWAA
Pricing	Slightly cheaper for notebooks	Cheaper for data storage

🛠️ Step-by-Step: Set Up Databricks Workspace

☁️ A. Azure Databricks Setup (Portal UI)

🔹 Step 1: Go to Azure Portal

Search for “Databricks” in Marketplace
Click Create Databricks Workspace
- Choose your resource group
- Select region (use same as ADLS for speed)
- Pricing Tier: Standard / Premium / Trial

🔹 Step 2: Azure Resources Created

Resource group
Virtual network + NSG (if enabled)
Managed Resource Group (auto-created)

🔹 Step 3: Launch Workspace

Click Launch Workspace → opens Databricks UI
Use AAD for login and user access control

🔹 Step 4: Mount ADLS Gen2

configs = {
  "fs.azure.account.auth.type": "OAuth",
  "fs.azure.account.oauth.provider.type": "org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider",
  "fs.azure.account.oauth2.client.id": "<app-id>",
  "fs.azure.account.oauth2.client.secret": "<secret>",
  "fs.azure.account.oauth2.client.endpoint": "https://login.microsoftonline.com/<tenant-id>/oauth2/token"
}
dbutils.fs.mount(
  source = "abfss://<container>@<account>.dfs.core.windows.net/",
  mount_point = "/mnt/data",
  extra_configs = configs)

☁️ B. AWS Databricks Setup (Console UI)

🔸 Step 1: Go to AWS Marketplace

Search “Databricks”
Subscribe to Databricks on AWS

🔸 Step 2: Use AWS Console to Launch Workspace

Choose VPC, Subnets, IAM roles
Define S3 Bucket for root storage

🔸 Step 3: Create EC2-backed Cluster

Workspace setup opens Databricks UI
Login with Databricks account (SSO optional)

🔸 Step 4: Mount S3 Bucket

ACCESS_KEY = "<aws-access-key>"
SECRET_KEY = "<aws-secret-key>"
ENCODED_SECRET_KEY = SECRET_KEY.replace("/", "%2F")
AWS_BUCKET_NAME = "my-databricks-bucket"
MOUNT_NAME = "s3"

dbutils.fs.mount("s3a://%s:%s@%s" % (ACCESS_KEY, ENCODED_SECRET_KEY, AWS_BUCKET_NAME),
                 "/mnt/%s" % MOUNT_NAME)

🔐 Security Comparison: IAM vs Azure AD

Topic	Azure Databricks	AWS Databricks
User Access	Azure AD Groups, AAD SSO	IAM Users / Databricks SCIM API
Data Access (Storage)	RBAC or SAS Token for ADLS	IAM Roles or Instance Profiles for S3
Secrets Management	Azure Key Vault integration	AWS Secrets Manager or Databricks Secrets
Network Isolation	VNet injection, NSG	VPC, Security Groups

📦 Cluster Setup Basics (Both Clouds)

Setting	Description
Cluster Mode	Standard, High Concurrency, Job
Runtime	Choose Databricks Runtime with Spark + Delta
Autoscaling	Enable for elastic compute
Spot Instances	Use for cost savings on AWS (Azure = Low Priority VMs)

💡 Use Cases and Real-World Examples

Use Case	Recommended Setup
Build unified Data Lake + ML System	Azure Databricks + ADLS + AAD + Unity Catalog
Cost-effective storage + compute	AWS Databricks + S3 + EC2 Spot + IAM
Multi-cloud support	Delta Lake format in either setup
Enterprise BI + RBAC compliance	Azure (easier governance with AAD)
Startups / Quick Prototyping	AWS Databricks with minimal setup

🧭 Pro Tip: Choosing Between Azure and AWS

Need / Preference	Go With…	Why
Strong Azure usage in org	Azure Databricks	Easier integration with AAD, Synapse, ADF
Open cloud flexibility + cheaper storage	AWS Databricks	S3 is cheaper and IAM is mature
Heavily regulated enterprise	Azure Databricks	Unified policy enforcement with Azure Security Center
Working with big AI/ML workloads	Either	Depends on cost control, but GPU support in both

🧪 Interactive: Try It Yourself

✅ Spin up a free Databricks trial on Azure or AWS
🧪 Load a sample CSV to S3 or ADLS
🔁 Convert CSV → Delta format
🔍 Use DESCRIBE HISTORY to view Delta versioning
💬 Comment your storage + cluster experience!

HintsToday

recent posts

about

DataBricks Tutorial for Beginner to Advanced