We use Deepnote for data science at our company, and it’s been a great experience. It’s easy and intuitive to use, and the UX is clean and well-designed. I also really like the color scheme. Review collected by and hosted on G2.com.

Larger notebooks can occasionally be slow to process. Even so, it hasn't caused a significant problem for our daily operations. Review collected by and hosted on G2.com.

Combining of SQL blocks and Python code is very seamless and easy to use. I believe the user experience overall was pretty good. It's easy for me to get the hang of it after just an hour of using and exploration. As well as how easy it is to integrate different platforms such as Snowflake and OpenAI into my projects. Review collected by and hosted on G2.com.

The Deepnote AI isn't too helpful at times. I would give it explicit information, for example, not to change a specific part of the code, yet it wouldn't read the prompt and change it anyway. It also has trouble sometimes reading the whole notebook but is okay with understanding a block. I would like an easier way for dependency blocks to be a thing where there could be a flowchart-type flow from top to bottom where it doesn't have to trigger every single block created. Review collected by and hosted on G2.com.

Deepnote is very intuitive and easy to get started with, which made the onboarding process smooth. It’s excellent for conducting analyses collaboratively and reaching conclusions together. Over time, the AI begins to understand my hypotheses and the structure of the database, which leads to increasingly relevant and insightful suggestions. It’s a powerful companion for exploratory analysis and decision-making. Review collected by and hosted on G2.com.

At the beginning, it requires more detailed explanations of your hypotheses and how the dataset works before the AI can provide useful suggestions. The prompts need to be very specific—for example, instead of saying “use the table above to create a scatter plot,” you need to reference the exact table name. Sometimes the AI freezes and runs indefinitely, requiring me to reset the notebook. I also find it difficult to stay organized when too many charts are generated, as I need to scroll a lot to find what I’m looking for. It would be very useful to have a dedicated space to organize the analysis into a document that combines written explanations with the corresponding charts. Review collected by and hosted on G2.com.

When I was looking to deploy Python apps and dashboards for a course, I found that there were few solutions easy for students to deploy and share. Deepnote's apps and dataframe visualizations are really neat and easy to deploy. I also really like the GitHub integration that makes it easy to share a project, rather than a single notebook. Review collected by and hosted on G2.com.

The environments are very opinionated and sometimes clash with projects that I've developed elsewhere. I'm seeing really fast development in this space -- especially, with the new VSCode support. Review collected by and hosted on G2.com.

We've been using Deepnote for a good while now, and my favourite feature is the ability to quickly and easily share code and visualisations with colleagues. This is really important to us as we use Deepnote for all our deeper A/B testing analyses, so being able to share results within the analytics team and also with product teams is super important. Recent AI-enabled features are a great add-on, although I'm yet to explore these fully. I also love being able to load in data from multiple sources and combine them in my notebooks. Review collected by and hosted on G2.com.

One thing that could be improved in Deepnote is the ability to find and store notebooks in projects more easily. With many analysts and scientists all using Deepnote, our folder structure has become pretty messy, especially since we don't have strong naming conventions for files. We have a lot of "Untitled Projects" laying around - some automation to help organise and tidy this up would be a great addition to a strong tool. Review collected by and hosted on G2.com.

Deepnote has a simple, unobtrusive UI that keeps the buttons out of the way, allowing you to focus on coding. The real-time collaboration features are outstanding, making it easy for multiple people to code together simultaneously. The main reason I prefer Deepnote is that it provides a cloud-based space for all my data science work, making it convenient to store, share, and manage even large files.

The Deepnote team pays great attention to user convenience. For instance, after using pip to install a package, Deepnote prompts you to add it to requirements.txt automatically. Then, whenever you restart the machine, it will auto-install that package for you. These small touches save a lot of time and mental effort. Review collected by and hosted on G2.com.

I find that Deepnote’s two main drawbacks are its slow performance and the constant need for an internet connection. I often experience lag, especially when collaborating with others or working on large, complex projects. This sluggishness disrupts my workflow and takes away from the collaborative strengths that drew me to Deepnote in the first place. Also, since Deepnote operates entirely in the cloud, I have to stay connected to the internet at all times. If my internet connection drops, I immediately lose access to my projects and data—unlike when I use local tools like Jupyter Notebooks, which let me work offline. These limitations sometimes interrupt my productivity and make Deepnote less suitable for me when I need instant feedback or the flexibility to work without an internet connection. Review collected by and hosted on G2.com.

Coming from Jupyter Notebook, I found Deepnote much more convenient for research in many ways. It was my first time doing research on a fully web-based platform, and I was very impressed—it felt far superior to Colab. File management and the overall experience stood out as particularly impressive. Review collected by and hosted on G2.com.

When compared to Cursor, the AI features feel very underpowered. The lack of an agent-like mode makes the workflow feel significantly less convenient. Review collected by and hosted on G2.com.

I really enjoyed using the platform, especially the integrated AI. I found the suggestions it provides to continue analyses very relevant and helpful, particularly when dealing with ambiguous scenarios. Another aspect I appreciate is that when the AI doesn't reach a satisfactory answer, it makes another attempt instead of stopping. Additionally, I value the auto-completion feature for coding, as it significantly speeds up the workflow. Review collected by and hosted on G2.com.

One point I believe could be improved is the need to frequently re-run the code because the tables are no longer saved. It feels like the time before they expire is too short. Another improvement would be the addition of a pivot table option in the available charting features. Lastly, having a functionality to hide code cells that we no longer need to edit would make the workspace much cleaner and easier to navigate. Review collected by and hosted on G2.com.

Deepnote is great because it lets multiple people work on the same notebook at the same time, just like Google Docs. It connects easily to tools like BigQuery, Google Sheets, and other databases without complicated setup. Since it runs in the cloud, there's no need to install anything—your work is always saved and accessible anywhere. Review collected by and hosted on G2.com.

Sometimes, Deepnote can be slower to load or run heavy computations compared to local notebooks. It also requires a stable internet connection since it's fully cloud-based. Lastly, while it's great for collaboration, some advanced users may find it less flexible than using raw Jupyter in their own environment. Review collected by and hosted on G2.com.

As someone with basic programming experience, DeepNote has been a great tool for helping me ease into Python coding. It offers a simple and intuitive way to get familiar with Python—not just as a new platform, but also as a practical tool to write the code I need. One of the features I love most is the integration with AI tools. Being able to ask a question and have the code generated instantly is incredibly empowering and time-saving. So, ease of use and ease of implementation and integration are key advantages of DeepNote in my opinion. Review collected by and hosted on G2.com.

So far, I haven't seen any downsides. I'm excited to continue using DeepNote and hope my experience remains just as smooth and productive in the future. Review collected by and hosted on G2.com.