Sign inGet started
← Back to all posts

Databricks vs Deepnote: A comparison for 2023

By Deepnote Team

Updated on November 3, 2023

Databricks vs. Deepnote: A 2023 Comparison

Databricks primarily utilizes notebooks for data science and machine learning workflows, offering real-time coauthoring, automatic versioning, and built-in data visualizations.

Deepnote is a collaboration-oriented data platform, providing a cloud-based workspace for data exploration, collaboration, interactive chart and dashboard creation, and machine learning model development and deployment.

AI Capabilities:
Both platforms offer AI assistance for coding. Both Databricks and Deepnote boast an advanced AI agent capable of creating SQL, Python, and text blocks, ensuring expected results and self-correction.

Jupyter Compatibility:
Both platforms are fully compatible with Jupyter, allowing seamless notebook uploading and usage.

Exploratory Coding:
Both platforms support Python and R. Databricks utilizes Jedi for coding assistance, while Deepnote relies on Codeium's AI code completion. Databricks additionally supports Scala.

Data Connection:
Both platforms provide a wide array of built-in data connectors for major cloud platforms, simplifying data source access.

Data Interaction and Visualization:
Both platforms include Notebook SQL blocks with code completion and built-in data frame outputs. They also offer built-in charting solutions and support various Python charting libraries.

Data Publishing:
Both platforms offer reporting and app tools, allowing scheduling, dashboard creation, and interactive dashboarding with fine-grained permission settings.

Both platforms prioritize collaboration, featuring fine-tuned permissions, collaborative notebooks, multi-user editing, and commenting.

Deepnote offers a free tier, a two-week trial with no credit card requirement, and permanent freemium options. Deepnote's team and enterprise plans combine seat and usage-based pricing.

Databricks provides a 14-day free trial and follows a pay-as-you-go model for pricing.

Read more about Deepnote, and Databrick's pricing.

In Conclusion:
Both Databricks and Deepnote are collaboration-focused data platforms with similar feature sets. The choice depends on specific requirements. Databricks excels with Scala support, while Deepnote offers a more advanced AI agent, and extensive integrations.


Illustrative image for blog post

Beyond AI chatbots: how we tripled engagement with Deepnote AI

By Gabor Szalai

Updated on April 3, 2024

That’s it, time to try Deepnote

Get started – it’s free
Book a demo



  • Integrations
  • Pricing
  • Documentation
  • Changelog
  • Security




  • Privacy
  • Terms

© Deepnote