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Azure ML vs Databricks: Which is Better in 2026?

Choosing between Azure ML and Databricks comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.

Bottom line: Databricks is our overall pick for data & databases workflows. Pick Azure ML if you need cloud & infrastructure.

··Methodology
Editor reviewed0 verified reviews comparedPricing checked Aug 2026

Short on time? Here's the quick answer

We've tested both tools. Here's who should pick what:

Azure ML

Cloud platform for building and deploying ML models

Best for you if:

  • • You need cloud & infrastructure features specifically
  • Azure ML is Microsoft's cloud platform for building and deploying machine learning models
  • It provides notebooks, AutoML, MLOps pipelines, and model management

Databricks

Unified analytics for data engineering, science, and ML

Best for you if:

  • • You need data & databases features specifically
  • Data and AI platform using consumption-based DBU pricing
  • Lakehouse combines data lake and warehouse on AWS, Azure, or GCP with Spark engine
At a Glance
Azure MLAzure ML
DatabricksDatabricks
Starts at
Custom
Custom
Best For
Cloud & InfrastructureData & Databases
Rating
4.4/54.6/5
Free plan
No No

Choose Azure ML or Databricks?

Azure ML

Choose Azure ML if

Cloud platform for building and deploying ML models

  • Enterprise ML platform
  • AutoML features
  • MLOps capabilities
  • Your work is cloud & infrastructure-shaped, not data & databases-shaped
Databricks

Choose Databricks if

Unified analytics for data engineering, science, and ML

  • Unified platform
  • Great collaboration
  • Delta Lake
  • Your work is data & databases-shaped, not cloud & infrastructure-shaped
FeatureAzure MLDatabricks
Pricing ModelPaidPaid
User Rating
4.4/5
117 reviews
4.6/5
1,385 reviews
Categories
Cloud & InfrastructureAI & Automation
Data & DatabasesAnalytics

In-Depth Analysis

Azure MLAzure ML

Cloud platform for building and deploying ML models

Starts at Custom
Good value

Azure ML's pricing model is fair and flexible, especially with a generous Free Tier and Pay-As-You-Go option starting at $0.

Watch out

Compute instance hours can accumulate quickly.

Strengths

  • +Enterprise ML platform
  • +AutoML features
  • +MLOps capabilities
  • +Designer for no-code
  • +Good model management

Weaknesses

  • -Expensive
  • -Complex
  • -Azure ecosystem required
  • -Learning curve
  • -UI can be slow

Key features

ML platformDesignerAutoMLMLOpsNotebooksMicrosoft

DatabricksDatabricks

Unified analytics for data engineering, science, and ML

Starts at Custom
Fair value

Databricks' pricing, particularly for All-Purpose Compute at $0.20-0.40/DBU and SQL Compute at $0.22-0.65/DBU, can quickly become expensive, and the separate cloud infrastructure bill for VMs, storage, and networking comes on top of DBU charges.

Watch out

Separate cloud infrastructure bill on top of DBUs, varying with instance types and usage

Strengths

  • +Unified platform
  • +Great collaboration
  • +Delta Lake

Weaknesses

  • -Expensive at scale
  • -Complex dual billing (DBU plus cloud infra)
  • -Steep learning curve

Key features

Unified analyticsDelta LakePhoton engineServerless computeMachine learningMosaic AI

Pricing: Azure ML vs Databricks

PlanAzure MLDatabricks
Tier 1
Free Tier
Community Edition
Tier 2
Varies
Pay-As-You-Go
/DBU
Jobs Compute
Tier 3
Custom
Enterprise
/DBU
All-Purpose
Tier 4N/A
/DBU
SQL Compute

Pricing verified from each vendor's public pricing page. Compare in detail on Azure ML pricing and Databricks pricing.

Who Should Use What?

On a budget?

Both are paid. Compare plans on their websites.

Go with: Databricks

Want the highest-rated option?

Azure ML: 4.4/5 (117 reviews). Databricks: 4.6/5 (1,385 reviews).

Go with: Databricks

Value user reviews?

Azure ML: 117 reviews (4.4/5). Databricks: 1,385 reviews (4.6/5).

Go with: Databricks

3 Questions to Help You Decide

1

What's your budget?

Both are paid. Pricing won't help you decide here.

2

What's your use case?

Azure ML is a cloud & infrastructure tool. Databricks is in data & databases. Pick the category that matches your needs.

3

How important are ratings?

Databricks is rated higher: 4.6/5 vs 4.4/5.

Key Takeaways

Databricks

  • Higher user rating: 4.6/5 vs 4.4/5
  • Larger review base (1,385 reviews)
  • Our pick for this comparison

Azure ML

  • Better fit for cloud & infrastructure

The Bottom Line

Databricks is our pick.

Frequently Asked Questions

Is Azure ML or Databricks better?

Databricks is rated in our evaluation. Both are paid.

What are Azure ML and Databricks used for?

Azure ML: Cloud platform for building and deploying ML models. Databricks: Unified analytics for data engineering, science, and ML.

What does Azure ML cost vs Databricks?

Azure ML is a paid tool. Databricks is a paid tool. Visit their websites for detailed pricing.

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