Deepnote
DeepnoteReviews from AWS customer
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Deepnote is a fantastic tool with a great free tier and reasonable paid tiers
What do you like best about the product?
Really easy to get started and just jump in and go. Lots of database connectors.
The unlimited VMs at the Pro size (4 vcpu, 16 GB) is perfect for everyday work.
The AI integration is the best across all competitors. We tested that integration out across 6 competitors and this is by far the best. It's awareness of the entire notebook's existing codebase, results and next steps is great. Other notebook tools typically struggle with a previous cell's output and you have to be really explicit and repeat code and/or results from previous cells to work with.
The apps feature is great to share content with non-technical users.
The unlimited VMs at the Pro size (4 vcpu, 16 GB) is perfect for everyday work.
The AI integration is the best across all competitors. We tested that integration out across 6 competitors and this is by far the best. It's awareness of the entire notebook's existing codebase, results and next steps is great. Other notebook tools typically struggle with a previous cell's output and you have to be really explicit and repeat code and/or results from previous cells to work with.
The apps feature is great to share content with non-technical users.
What do you dislike about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
Data analysis. Data science and machine learning around large data sets. Reporting interface for data in the database before building it out in the application layer.
Nice and Simple for Entry-Level Roles
What do you like best about the product?
Deepnote is easy to use and learn. Lots of customizable features and uses. As an entry-level employee— it's been an extremely helpful tool, as well as one that has been easy to adjust to and customize.l
What do you dislike about the product?
No big downsides so far. It is relatively easy to use. Looking forward to continue exploring it.
What problems is the product solving and how is that benefiting you?
Deepnote assists in tracking campaigns and performance. I particualrly enjoy the ability to create shareable dashboards. Python projects are also very easy to run and manage.
Best notebook used so far
What do you like best about the product?
- the handy concept of a SQL+Python notebook.
- the collaboration is very smooth
- the viz module directly from the data
- the autocompletion and the debugger, backed by AI
- Notion integration
- the collaboration is very smooth
- the viz module directly from the data
- the autocompletion and the debugger, backed by AI
- Notion integration
What do you dislike about the product?
- The app concept, which the exported notebook with interactivity (filters etc) is a bit complex, we often struggle to have our non-tech stakeholders to use it as they just use it for that and it's used often.
What problems is the product solving and how is that benefiting you?
It help exploring the data in a much quicker, cleaner and collaborative way
Best jupyter notebook solution
What do you like best about the product?
the IA, is most capable so non tech persons automates apis, etls, flows in their own.
What do you dislike about the product?
They have changed their policiy about auto shutting down vm, now is too short. I suppose depends on the service tier.
What problems is the product solving and how is that benefiting you?
Colaborative place with very good AI
One of new AI tools I use daily
What do you like best about the product?
I’ve been using Deepnote regularly, and it’s made a significant difference in how I handle my daily tasks. The platform is user-friendly, so working with data feels intuitive even if you’re not highly technical. I appreciate that they’re constantly updating the tool, which means it keeps getting better and stays relevant to my needs.
Collaborating with my team has become much smoother thanks to Deepnote’s clear and straightforward tools. Sharing notebooks and working together in real-time has improved our efficiency and the quality of our projects.
Integrating with BigQuery was surprisingly easy. Managing the integration credentials didn’t require much effort, which saved me time and avoided the usual hassle of connecting different services.
The AI-assisted code generation is a feature I’ve found particularly useful. It speeds up my coding process and makes it easier for team members who might not have a strong technical background to contribute.
Overall, Deepnote has become an essential part of my workflow. It’s helped make my work more streamlined and productive, and I highly recommend it to others looking to enhance their data analysis and team collaboration.
Very good and simpel user based pricing model that allows us to share some notebooks/projects to users for free as well which is very imporant for us.
Collaborating with my team has become much smoother thanks to Deepnote’s clear and straightforward tools. Sharing notebooks and working together in real-time has improved our efficiency and the quality of our projects.
Integrating with BigQuery was surprisingly easy. Managing the integration credentials didn’t require much effort, which saved me time and avoided the usual hassle of connecting different services.
The AI-assisted code generation is a feature I’ve found particularly useful. It speeds up my coding process and makes it easier for team members who might not have a strong technical background to contribute.
Overall, Deepnote has become an essential part of my workflow. It’s helped make my work more streamlined and productive, and I highly recommend it to others looking to enhance their data analysis and team collaboration.
Very good and simpel user based pricing model that allows us to share some notebooks/projects to users for free as well which is very imporant for us.
What do you dislike about the product?
As a relatively new tool Deepnote has some shortcomings and not-so-ready features. File management and Git integration are some examples. There have been some improvements in these areas though.
What problems is the product solving and how is that benefiting you?
Easy access for our data warehouse and services.
Easy prototyping -- with the team.
Ability to easily make simple data apps and share access to our team.
Easy prototyping -- with the team.
Ability to easily make simple data apps and share access to our team.
Great data environment for teams and a level-up from Jupyter notebooks
What do you like best about the product?
Easy to use for team members new to notebooks
What do you dislike about the product?
Would love to see greater support for historical notebook runs to save itteration and cold-boot time
What problems is the product solving and how is that benefiting you?
Easy to integrate with multiple data sources and to collaborate across the team on shared notebooks, whereas this would be dispirate across team members for Jupyter notebooks.
Very user-friendly & intuitive cloud platform - great for collab
What do you like best about the product?
What I love most about Deepnote is how easy it is to collaborate with my team in real-time—it really streamlines the whole process and boosts our productivity. The interface is super intuitive, so even if you're not a coding expert, you can still get up to speed quickly. Another big plus is how well it connects with different data sources, making it simple to set up data analysis workflows. Because it's cloud-based, I don’t have to deal with complicated local installs, which is a huge time-saver. I also find the AI tools really handy for code suggestions and debugging, making it quicker to write and fix code.
What do you dislike about the product?
Nothing much,
Could perhaps do with some additional viz capabilities to analyse your data but not a big deal
Could perhaps do with some additional viz capabilities to analyse your data but not a big deal
What problems is the product solving and how is that benefiting you?
We use Deepnote mainly for AI-enrichment of our GTM data, along with data cleansing and modeling. It's been a helpful tool in our workflow, making it easier to clean up data and add valuable insights before analysis. I like how we can build and tweak models directly in Deepnote, which helps keep our data processes smooth and efficient.
Well Organized Notebook and Code Space that Efficiently Blasts Through Visualization and Latex Work
What do you like best about the product?
The most helpful: The embedded Chat GPT AI enables me to move extremely quickly to do complex visualizations across meshgrids, quickly turn collected data into data frames, and after providing clear examples of the backend code or functions I would like to run, is able to permute or iron out my work. Basically Deepnote lets me work really quickly, given I know what I'm trying, and then share the results cleanly. Saves me so much time.
What do you dislike about the product?
It used to be that the AI generation window would cover error messages. I believe that's been improved. In addition it used to be that as you typed text it would always try to autocomplete, which would be distracting for non code text. That has also been made optional.
Right now it's that the performance for long notebooks ("Deep Notebooks") can get really bad, especially on Chrome on Linux. It can get to the point where I can't open some of my notebooks in Chrome because they will just crash the browser.
Also, I would like the table of contents feature to be an optional hover window so I can see it anywhere. For DeepNotes with lots of variables, having to scroll through all the variables to get to the table of contents defeats the purpose of the table of contents in the first place.
Right now it's that the performance for long notebooks ("Deep Notebooks") can get really bad, especially on Chrome on Linux. It can get to the point where I can't open some of my notebooks in Chrome because they will just crash the browser.
Also, I would like the table of contents feature to be an optional hover window so I can see it anywhere. For DeepNotes with lots of variables, having to scroll through all the variables to get to the table of contents defeats the purpose of the table of contents in the first place.
What problems is the product solving and how is that benefiting you?
I use Deepnote for many different problems. 1) Performing visualizations, analysis, and developing models or conclusions. Typically I import data into dataframes and then use that data to perform engineering calculations or train models. I then do visualizations of my results. A common case I use it for is optimization for controls and design synthesis problems. I then mix my work with headers and Markdown for organization, and then share my notebooks as Apps.
Deepnote mostly handles all of the very tedious time consuming steps (Data wrangling and plotting) via its ChatGPT integration. Chat GPT is not currently trustable for my mission critical backend optimization or modelling code, but once I have written backend functions, it is able to use those examples, and Deepnote then is able to help me quickly refine and visualize until I get my desired results.
Deepnote mostly handles all of the very tedious time consuming steps (Data wrangling and plotting) via its ChatGPT integration. Chat GPT is not currently trustable for my mission critical backend optimization or modelling code, but once I have written backend functions, it is able to use those examples, and Deepnote then is able to help me quickly refine and visualize until I get my desired results.
The Best Collaborative Data Science Platform Out There!
What do you like best about the product?
Deepnote has completely transformed my workflow as a data scientist. It combines the functionality of traditional Jupyter notebooks with powerful collaborative features, making it an essential tool for any data science team. The platform is incredibly intuitive, with a clean interface and built-in support for all major data science libraries.
One of the standout features is real-time collaboration – I can work alongside my teammates just like in Google Docs, which has significantly boosted our productivity. Setting up projects is seamless, and Deepnote handles the back-end configurations, so we can focus entirely on data exploration and analysis.
The integration with various data sources, from databases to APIs, is smooth and easy to manage, saving us so much time on setup. The support team is also highly responsive and genuinely cares about user feedback, frequently rolling out updates that make the platform even better.
Whether you’re a beginner or a seasoned data professional, Deepnote will elevate your projects. Highly recommend it to anyone looking for a reliable, efficient, and collaborative data science environment!
One of the standout features is real-time collaboration – I can work alongside my teammates just like in Google Docs, which has significantly boosted our productivity. Setting up projects is seamless, and Deepnote handles the back-end configurations, so we can focus entirely on data exploration and analysis.
The integration with various data sources, from databases to APIs, is smooth and easy to manage, saving us so much time on setup. The support team is also highly responsive and genuinely cares about user feedback, frequently rolling out updates that make the platform even better.
Whether you’re a beginner or a seasoned data professional, Deepnote will elevate your projects. Highly recommend it to anyone looking for a reliable, efficient, and collaborative data science environment!
What do you dislike about the product?
Honestly, there’s very little to dislike about Deepnote! If I had to pick something, it would be great to see even more customization options for themes and layout preferences. But even as it stands, Deepnote’s design and functionality are top-notch.
What problems is the product solving and how is that benefiting you?
Real-Time Collaboration,Seamless Integration, Enhanced Code Management, AI-Powered Assistance
Intuitive Collaboration for Data Projects
What do you like best about the product?
Deepnote offers an incredibly intuitive platform for collaborative data analysis, making it easy to share projects and insights with team members. The real-time collaboration feature is particularly useful, allowing multiple users to work on a notebook simultaneously without issues. The integration capabilities with tools like SQL, Python, and data visualization libraries make it versatile for various data needs, from exploration to presentation. The interface is also very user-friendly, which lowers the learning curve for new users, whether they're analysts or product managers."
What do you dislike about the product?
While Deepnote excels in collaboration, there are a few areas that could be improved. The platform can occasionally be slow when handling very large datasets, which impacts productivity. Additionally, while it integrates well with many data sources, it would be beneficial to have more customization options in the data visualization aspects, as the current capabilities can feel limited for advanced visualizations. Lastly, the cost for enterprise features can be a bit steep, which might be a barrier for smaller teams.
What problems is the product solving and how is that benefiting you?
Deepnote is solving several key problems for our data-driven projects, primarily by enhancing collaboration, simplifying data access, and reducing technical barriers. In a typical data analysis workflow, sharing insights and working in real-time with teammates can be cumbersome, especially when using traditional tools. Deepnote's collaborative environment allows multiple users to seamlessly work together in a single notebook, eliminating version control issues and making it easy to get feedback instantly.
Another major benefit is its integration with various data sources and tools (SQL databases, APIs, and cloud storage), which streamlines data access and reduces the time spent on data preparation. This enables us to focus more on analysis and insights rather than data wrangling. For me, as a Product Manager, it’s invaluable to have a platform where I can quickly access up-to-date information and collaborate with analysts on reporting and visualization, which ultimately speeds up decision-making and helps deliver better insights to stakeholders.
Another major benefit is its integration with various data sources and tools (SQL databases, APIs, and cloud storage), which streamlines data access and reduces the time spent on data preparation. This enables us to focus more on analysis and insights rather than data wrangling. For me, as a Product Manager, it’s invaluable to have a platform where I can quickly access up-to-date information and collaborate with analysts on reporting and visualization, which ultimately speeds up decision-making and helps deliver better insights to stakeholders.
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