Deepnote Reviews & Product Details

Deepnote makes pulling and exploring data so much easier. We can quickly connect to databases and get straight into analysis, which has really improved our visibility into performance and helped speed up decision-making. It’s also incredibly flexible — we’ve been able to build models that help ensure operational quality and adapt them as our needs evolve. Plus, the real-time collaboration, SQL/Python support, and zero setup make it perfect for remote teams. Review collected by and hosted on G2.com.

The main issue is the loading time when working with larger datasets or multiple data sources — it can be a bit slow to initialize. Also, since it’s fully cloud-based, it doesn’t work well in low-connectivity situations, and offline access would be a helpful addition. Review collected by and hosted on G2.com.

I've been using Deepnote for my Python projects, and it's been an absolute game-changer. The interface is clean, intuitive, and incredibly well-suited for both solo work and team collaboration. I especially love the real-time collaboration features—feels like Google Docs for data science. It also integrates smoothly with popular tools like GitHub and BigQuery, which saves me a lot of time. The fact that I can run Jupyter-style notebooks in the cloud without setting up a local environment is a huge plus. Highly recommend it for anyone working on data science, analytics, or machine learning workflows. Review collected by and hosted on G2.com.

sometimes a little slow but its a good feature to work with. Review collected by and hosted on G2.com.

It provides great visualization tools for notebooks, with some nice features like column summarization. It also lets you group many notebooks in the same project, something that its competitors don't let you do. Its AI features are better than competitors too, it can create a full analysis in its own. Review collected by and hosted on G2.com.

Despite the fact that the AI is way better than its competitors, it's still somewhat clunky to use, can create many unused cells and leave them there. Also, some features are missing/are not the defaul:

- i should be able to query (join) every dataframe in SQL

- cell replay should replay its children by default Review collected by and hosted on G2.com.

Deepnote is a genuinely useful application of AI in coding, in terms of predictive code suggestions I've never come across anything like it and the time it saves building out queries is exceptional. It was an easy set up and integration and it's an intuitive interface that doesn't take long to familiarise yourself with. The file structure makes it easy to quickly run ad hoc queries on once off data sets while the multiple integrations and project structure make bigger projects a breeze. Would quite literally now be lost without it. Review collected by and hosted on G2.com.

The only things I dislike really are smaller nitpicks rather than feature gaps. The menu to convert/duplicate code blocks is a little clunky and the "fix my code" AI is not as effective as the predictive piece. Review collected by and hosted on G2.com.

Deepnote's AI assistant has been incredibly helpful in creating new code blocks and fixing issues, making it easier to manage the ETL process without prior extensive Python experience. The platform allows for smooth daily execution of the ETL process, which has been running reliably. The built-in secret management helps avoid hardcoding secrets directly into the code, providing a basic level of security. Review collected by and hosted on G2.com.

The interface can be slow to load, especially with a large number of code blocks. I wish I could get detailed information about past executions, both successful and failed, for troubleshooting and monitoring. The visibility of secrets in the secret manager poses a potential security risk. Review collected by and hosted on G2.com.

The best part of using deepnote is to be able to combine different environments such as Python, SQL, files, etc. to be able to develop much faster. Also, the automation of tasks is very useful and allows you to keep track of errors very easily. I'm a hard user of Deepnote since I knew it. Also, the integrations are really useful and have everything I need. Review collected by and hosted on G2.com.

The AI functions are useful, but need to be improved. Sometimes I don't feel confident with this. Also, I would like to have more options to automate processes like ETL that are long-time-running projects but could be executed very easily with such a tool.

Also, plots could be limited and sometime I have to use python because plot feature is not enough. Review collected by and hosted on G2.com.

I really appreciate the level of control Deepnote gives me when running analyses and creating internal user-facing data apps. It's easy to reuse code blocks, connect to external data sources, and spin up visualizations in a matter of minutes. I've been using some version of Python notebook tools for ~15 years and I find Deepnote to be quite intuitive for someone like myself. Review collected by and hosted on G2.com.

The number one challenge I've had, and this is probably based on me being newer to Deepnote (having used Hex pretty extensively over the past 4 years), is project management. For example, created a notebook in the wrong project and I could not find a simple way to export that notebook from one project into another -- I ended up having to copy the whole project and delete everything I didn't need. In the same vein, not being able to have more than 1 live data app per project seems strange. For example, I build a notebook app and wanted to create a version for internal metrics that provides an overview of all clients, but then have a version that is per-client specific. Those need to live in different projects to be published. Perhaps it's just me not being as familiar with the project management aspect of Deepnote, but it felt like a bit of overhead that can be simplified with some UX work to improve the "speed to value" for users that create multiple data apps. Review collected by and hosted on G2.com.

Deepnote enables us to collaborate efficiently on data analyses for customer projects. The cloud-based environment is modern and clearly designed. Particularly helpful is the ability to share notebooks directly with colleagues and work on them together. The integration of various data sources works well and saves time on project work. Review collected by and hosted on G2.com.

Occasionally, the loading times for larger datasets could be optimized. Some advanced features are only available in higher pricing tiers. The offline functionality is naturally limited, as it is a cloud solution. Review collected by and hosted on G2.com.

I love how I can create a shared environment with my teammate, and we don't have to worry about staying in sync. We have real-time visibility into what the other is doing and can set up duplicate notebooks and roll back changes easily. Jupyter is great on its own for code generation; it's that much more valuable in a shared environment. Review collected by and hosted on G2.com.

The startup is very slow, as it loads all our dependencies. This wouldn't be such a big deal if the machine didn't shut down every 15 minutes. In theory, it's supposed to load the cache, but I haven't gotten that to work. I also could not get the integration with Google Drive to work. It was showing an error, so I ended up using an API instead. Review collected by and hosted on G2.com.

It became the one stop shop source of all our strategies in Debt Collections. We are able to segment, create many ways to manage the accounts endorsed to us making it easy to load in our tools and ensure all details and data are captured well Review collected by and hosted on G2.com.

Sometime server is down therefore need to restart entire laptop or wait for it to resume Review collected by and hosted on G2.com.