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.

Versatility of the tool to write SQL and python code, as well as connecting to multiple data sources.

The AI features also provides more autonomy for less tech/data savvy teammembers. Review collected by and hosted on G2.com.

Lack of more options of tools/widgets/cells to explore data more freely. One example is the lack of a pivot table component. 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.

Allows custom docker images with custom kernels Review collected by and hosted on G2.com.

charts UI is not very polished and customizable 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.

Direct integration with BigQuery, very intuitive Python notebook and App functionality to share dashboards with the team. Review collected by and hosted on G2.com.

Apps have to be rerun every time. It would be great if they kept past runs and / or could be scheduled (once a day for example). Some dashboards take 3+ minutes to load. Review collected by and hosted on G2.com.

I appreciate that you can perform statistical analysis and generate the corresponding graphs. Review collected by and hosted on G2.com.

I believe there should be more promotion, as it is still somewhat unknown. Review collected by and hosted on G2.com.