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Deepnote vs Databricks: Which is Better in 2026?

Choosing between Deepnote 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 Deepnote if you need analytics.

··Methodology
Editor reviewed0 verified reviews comparedPricing checked Jun 2026

Short on time? Here's the quick answer

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

Deepnote

Collaborative analytics and data science notebook for the AI era.

Best for you if:

  • • You want to try before committing
  • • You need analytics features specifically
  • AI-powered collaborative data science notebook supporting Python, SQL, and R.
  • Transforms data explorations into interactive data apps and dashboards.

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 from $0.07 to $0.65+/DBU
  • Lakehouse combines data lake and warehouse on AWS, Azure, or GCP with Spark engine
At a Glance
DeepnoteDeepnote
DatabricksDatabricks
Starts at
FreeFree tier available
Custom
Best For
AnalyticsData & Databases
Rating
4.5/54.6/5

Choose Deepnote or Databricks?

Deepnote

Choose Deepnote if

Collaborative analytics and data science notebook for the AI era.

  • AI assistance significantly speeds up data analysis and coding tasks.
  • Seamless collaboration features make teamwork efficient.
  • Supports a wide range of data sources and languages.
  • You want a free tier before you commit
  • Your work is analytics-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 analytics-shaped
FeatureDeepnoteDatabricks
Pricing ModelFreemiumPaid
User Rating
4.5/5
378 reviews
4.6/5
667 reviews
Categories
AnalyticsDeveloper Tools
Data & DatabasesAnalytics

In-Depth Analysis

DeepnoteDeepnote

Collaborative analytics and data science notebook for the AI era.

Strengths

  • +AI assistance significantly speeds up data analysis and coding tasks.
  • +Seamless collaboration features make teamwork efficient.
  • +Supports a wide range of data sources and languages.
  • +Ability to create interactive data apps and dashboards from notebooks.
  • +Strong security and compliance features suitable for enterprises.

Weaknesses

  • -Limited Deepnote AI features and compute resources in the free tier.
  • -Advanced security and deployment options are only available in higher-tier plans.
  • -Reliance on cloud infrastructure may not suit all data governance requirements without custom deployments.

Key features

AI-powered code generation, explanation, refactoring, and debuggingSupport for Python, SQL, and R in a single IDEInteractive visualizations and no-code configurable chartsCreation and deployment of data apps and dashboardsScheduled notebooks and API deployment for modelsReal-time collaboration, commenting, and version history
Starts at Free

DatabricksDatabricks

Unified analytics for data engineering, science, and ML

Strengths

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

Weaknesses

  • -Expensive
  • -Vendor lock-in

Key features

Unified analyticsDelta LakeMachine learningSQL analyticsData engineeringCollaborative notebooks
Starts at Custom

Pricing: Deepnote vs Databricks

PlanDeepnoteDatabricks
Tier 1
Free
Free
Community Edition
Tier 2
$39 per editor/month billed yearly
Team
/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 Deepnote pricing and Databricks pricing.

Who Should Use What?

On a budget?

Deepnote has a free tier. Databricks is paid only.

Go with: Deepnote

Want the highest-rated option?

Deepnote: 4.5/5 (378 reviews). Databricks: 4.6/5 (667 reviews).

Go with: Databricks

Value user reviews?

Deepnote: 378 reviews (4.5/5). Databricks: 667 reviews (4.6/5).

Go with: Databricks

3 Questions to Help You Decide

1

What's your budget?

Deepnote is freemium. Databricks is paid. Deepnote lets you start free.

2

What's your use case?

Deepnote is a analytics 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 4.5/5.

Key Takeaways

Databricks

  • Higher user rating: 4.6/5 vs 4.5/5
  • Larger review base (667 reviews)
  • Our pick for this comparison

Deepnote

  • Has a free tier
  • Better fit for analytics

The Bottom Line

Databricks is our pick. Deepnote has a free tier if you want to test without paying.

Frequently Asked Questions

Is Deepnote or Databricks better?

Databricks is rated in our evaluation. Deepnote is freemium and Databricks is paid.

What are Deepnote and Databricks used for?

Deepnote: Collaborative analytics and data science notebook for the AI era.. Databricks: Unified analytics for data engineering, science, and ML.

What does Deepnote cost vs Databricks?

Deepnote is freemium (free tier + paid plans). Databricks is a paid tool. Visit their websites for detailed pricing.

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