Pricing score

Deepnote Pricing Profile

Deepnote is a powerful, cloud-based platform that emphasizes collaborative data science. It provides teams with a rich set of tools for working together on notebooks, integrating with external data sources, and deploying machine learning models, all in a seamless and scalable environment.

HQ Location

San Francisco, California, USA

Category:

Key Takeaways

Cloud-Based Environment

Being cloud-based, Deepnote eliminates the need for local setup, hardware, or dependency management. It enables instant access to your notebooks from anywhere with a web browser.

Data Integration

Deepnote integrates seamlessly with popular data sources, such as Google Drive, AWS S3, GitHub, and BigQuery, allowing you to work directly with datasets from cloud storage or external databases.

Version Control

Deepnote provides built-in version control, allowing you to track changes to your notebooks and revert to previous versions. It also integrates with GitHub to sync and manage your project repositories.

Product Overview

Deepnote enables teams to work together on data projects in real-time. Multiple users can edit the same notebook simultaneously, making it ideal for team-based workflows and sharing insights.

In addition, Deepnote supports a variety of programming languages, including Python, R, and SQL, making it versatile for different use cases, from machine learning to data exploration.

INSIGHTS

Our insights about Deepnote pricing

Free trial

Custom options

Free plan

Available Pricing Models

How much does Deepnote cost?

Deepnote offers a free plan for the up-and-coming and hobbyist data scientists. It includes up to 3 editors, up to 5 projects, AI-powered code completion, unlimited Basic machines with 5 GB RAM, 2 vCPU and 7 day revision history.

Team

For individuals and data teams who need powerful integrations with their stack and seamless collaboration.
$39 per editor/month.

Enterprise

For organizations that require additional security, compute, and deployment options.
Custom pricing.

What users say about Deepnote pricing

Grigory M.

Previously used Jupyter Notebook and PyCharm. Would like to say that Deepnote is more convenient, you just create python or SQL cell in a matter of seconds. Making new integrations is also mostly very easy. UI is very straightforward and user-friendly, everything that is often needed in everyday work is by your hand (table schemas, timetables for your script, integrations, etc.)

Martin D.

Deepnote has truly transformed the way I work with data. Its user-friendly interface is both intuitive and visually appealing, making it a joy to navigate even the most complex tasks. The platform's speed and efficiency are unmatched, allowing me to focus on insights rather than waiting for processes to complete.

Arthur L.

It's very easy to set up, great for collaboration and inexpensive when compared to other data science tools, not to mention intuitive. I use it to call APIs and capture and send data to our BI tool, and compared to what the tool would charge us to have Python in their platform, Deep note is virtually free.

Bálint T.

I have been using Deepnote for more than a year and I'm super satisfied with it. It's easy to connect to our data watehouse and run our first line of code. Deepnote AI makes data exploration way faster, we are power user of the App function. Several applications are used across the organisation. Notebook scheduling is also extremely useful for us with integrating Deepnote to Slack and Notion. We were able to create a fully automated reporting for our stakeholders.

David S.

There is one competitor that works better with Snowflake by integrating directly with Snowpark by translating python code to run on-warehouse instead of on the VM. If you have large data sets, it's better to run it on the warehouse. You can just explicitly run Snowpark code in the notebook but it's not "magic" so it doesn't just translate it for you. For me, that's fine. I'd rather run it on the VM anyways and know exactly where my code runs but I could see folks who don't want to write all that extra code.

Grigory M.

Bálint T.

Martin D.

David S.

Arthur L.

Deepnote Pricing Rating

Scalability: 4.8/5

With Deepnote’s cloud compute resources, you can scale your projects and computations as needed without worrying about managing infrastructure or hardware.

Productivity: 4.7/5

The platform’s focus on real-time collaboration, version control, and integration with various data sources increases the productivity of data science teams, allowing for faster iteration and sharing of insights.

Collaboration-First: 4.9/5

Deepnote is designed for teams that need to collaborate on data science projects. With real-time collaboration, shared workspaces, and communication features, it's perfect for cross-functional teams working together on data-driven projects.

FAQ on Deepnote Pricing

How does Deepnote support collaboration?

Deepnote enables real-time collaboration, allowing multiple users to edit the same notebook simultaneously. Team members can leave comments, track changes, and work together on projects without switching between different tools or platforms.

Does Deepnote support Jupyter Notebooks?

Yes, Deepnote is compatible with Jupyter Notebooks. You can import, run, and edit Jupyter Notebooks in Deepnote without any issues, making it easy to transition from Jupyter to Deepnote.

What programming languages does Deepnote support?

Deepnote supports Python, R, and SQL, which makes it versatile for a wide range of data science, machine learning, and analysis tasks.

Can I use Deepnote without installing anything?

Yes, Deepnote is cloud-based, which means there is no need for local installation. You can access and work on your projects directly from your web browser, with all dependencies and environments managed in the cloud.