Deepnote Reviews & Product Details

Deepnote makes collaboration on data science and research projects effortless. I really like its real-time editing, version control, and easy cloud-based setup. It’s great for teaching, code reviews, and sharing results without complex configuration. Review collected by and hosted on G2.com.

Sometimes, large datasets can cause slower performance, and offline access options are limited. Review collected by and hosted on G2.com.

Deepnote has been one of the most useful tools in my daily workflow.

As an Account Manager in a SaaS company, having access to accurate information is essential for making decisions. Deepnote has helped me make data-driven decisions by providing clear numbers and actionable insights, allowing me to rely on facts and accurate projections. Review collected by and hosted on G2.com.

Sometimes, it takes longer than it should to load the data, especially early in the mornings. Review collected by and hosted on G2.com.

I've used Deepnote for everything from one-off dashboards for clients to big solo projects that involve stitching together data from multiple sources. It allows easy switching between Python and SQL in the same notebook (and maybe R? I haven't tried that yet though!). It is also straightforward to integrate external data from Sheets or Snowflake or what-have-you. There is also a lot of options for power users who need more computing power, though I have found the out-of-the-box ones to be plenty powerful for most of my needs.

The interface is clean and intuitive, and there is good documentation. The Deepnote team is busy and updates and improvements come regularly. I've had limited interaction with customer service, but the couple times I have they have been fast and helpful and understanding. Review collected by and hosted on G2.com.

Some nitpicky things . . . The built-in charts have been improving, but I'd still love LOTs more in this department, especially for snazzy interactive charts. They also do not yet support iPywidgets, which I've frequently wanted for small projects. They provide a smaller subset of similar input tools built-in, but not nearly enough. Lastly, I'd love slightly better notebook layout tools, specifically the ability to create collapsible sections without fiddling with HTML. Review collected by and hosted on G2.com.

The platform is easy to set up, and I appreciate being able to use both SQL and Python. Deepnote AI is also extremely helpful, especially when it comes to debugging and quickly visualizing data. Review collected by and hosted on G2.com.

There isn't much to add at this point, but I'm interested to see how Deepnote AI develops in the future. Occasionally, it has difficulty keeping up with multiple follow-up requests, yet overall, my experience has been positive. Review collected by and hosted on G2.com.

I've used several different notebooks: jupyter, databricks, colab, kubeflow. Out of everything I have tried, Deepnote gives me what I need. It is easiest for collaboration, easiest for scaling appropriately, easiest for choosing different environments and getting set up. It is just what I need, and I hope they keep improving it in these practical ways. Review collected by and hosted on G2.com.

It costs a bit much for the first tier past free. I am an individual, and not comfortable paying so much per month just to collaborate with a few people. It should cost about half that, to be more comfortable to individuals. I'd pay $25 per month, not $50. Review collected by and hosted on G2.com.

Deepnote is very easy to use wheather a beginner just starting out or professional Data Scincetist working on a project for your company. One of the best parts of Deepnote is there many intergration you can connect to, google drive if your just starting out or connect to the many SQL services. Their visual allow you to bring your data to life and see everything in real-time, it even updates in real-time which makes it every sharp. The ease of getting start quickly and running your project is immediate, which is one thing appreicate about Deepnote, its just a few seconds before your digging into the data. Review collected by and hosted on G2.com.

One thing I would like Deepnote to add is more visual into their built in platform is more ways to visual the data. getting location maps,heatmaps etcs. It seem that deepnote is more professional and not really collage students going into the sciences, I would have love to use deepnote while in collage I never knew it was around and to go out and look for alternative. Review collected by and hosted on G2.com.

I've been using Deepnote for over a year now, mostly for Python projects. At first, I just used it to schedule and automate scripts for different tasks. As we grew, it turned into a go-to tool for running Python scripts, and even our non-technical teammates can now run scripts on their own without needing my help.

The interface is clean and easy to use, the built-in integrations are super handy, and having secret key management built in is a big plus.

I also really like the AI features — they help me write code faster by predicting what I need and are great for debugging when something goes wrong. The customer support also great, while they are not available during my working hours, but they will respond as soon as they are available. Review collected by and hosted on G2.com.

Sometimes the interface is a bit slow to load and can feel laggy. One thing I’m also concerned about is how secret keys are handled — it would be better if only the owner could view the actual values, while others could still use them without seeing the details.

I've also run into a few issues when moving scripts from VS Code to Deepnote. Even with the same Python version, some scripts that work perfectly in VS Code throw errors in Deepnote, which means I have to spend extra time debugging. Because of that, I’ve ended up relying on Deepnote more for testing just to avoid those additional time required. Review collected by and hosted on G2.com.

- Multiple people can edit the same notebook at once, see each other’s cursors, and comment.

- No local configuration nightmares - packages and environments are managed in the cloud, so you can start working immediately.

- Built-in connectors to BigQuery, Snowflake, PostgreSQL, Google Sheets, etc., make it easy to pull data without juggling API keys and drivers. Review collected by and hosted on G2.com.

- Processing very large dataframes can feel slower than a well-tuned local Jupyter setup.

- You can hit memory or runtime caps quickly if you’re doing heavy ML or large ETL work unless you upgrade to higher-tier plans.

- Converting notebooks to .ipynb or other formats works, but sometimes you lose small bits of formatting or Deepnote-specific features. Review collected by and hosted on G2.com.

What I like most about Deepnote is that it feels like a supercharged version of Jupyter Notebooks. I use it daily at work to automate processes, connect to APIs, generate reports, and trigger actions. It’s very intuitive and user-friendly, even compared to other tools like Colab or Jupyter Lab. The built-in data visualizations are powerful and make analysis much easier. It was very easy to get started with—no complex setup or configuration was needed, so the ease of implementation was excellent. Everything just worked right out of the box.

On the few occasions I needed help, the customer support was responsive and helpful. Their team showed a great attitude and helped me resolve the issue quickly. Review collected by and hosted on G2.com.

Overall, I’m very satisfied and haven’t had major issues. I did run into some difficulty integrating Google Sheets directly, but it was likely due to a lack of documentation or research on my part. I worked around it using the Google API. Also, while I don’t use the collaboration features much, they could be useful for team-based projects. Review collected by and hosted on G2.com.

What I love most about Deepnote is its seamless real-time collaboration features combined with its intuitive interface. The ability to work simultaneously with team members on Jupyter notebooks while having built-in version control and commenting systems has completely transformed how we approach data science projects. The platform's integration with popular data sources and cloud services, along with its powerful compute resources, makes it incredibly easy to go from data exploration to production-ready insights without the usual infrastructure headaches. Review collected by and hosted on G2.com.

While Deepnote is fantastic overall, there are a few minor areas for improvement. The pricing can become steep for larger teams or when requiring extensive compute resources for extended periods. Occasionally, I've experienced slight lag during peak usage times, and some advanced customization options that power users might expect from local Jupyter environments are still limited. Review collected by and hosted on G2.com.