Deepnote vs. Shakudo Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Deepnote
Score 0.0 out of 10
N/A
Deepnote is a data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud.N/A
Shakudo Platform
Score 6.0 out of 10
N/A
The Shakudo platform ensures compatibility across data tools to allow companies to build the best data infrastructure for their needs. It supports over 60 popular data tools, and enables users to create the optimal data stack for any custom needs, and helps users to create a more reliable and performant stack. And it helps users to: Build a stack that works precisely for the company without worrying about maintenance costs or stability Using a single UI, let teams use and gain…N/A
Pricing
DeepnoteShakudo Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DeepnoteShakudo Platform
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesYes
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Best Alternatives
DeepnoteShakudo Platform
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Testimonials
DeepnoteShakudo Platform
ScreenShots

Deepnote Screenshots

Screenshot of

Shakudo Platform Screenshots

Screenshot of Shakudo Platform Dashboard UIScreenshot of Jobs use the same environment config as Sessions, so users can have the same dependencies and configurations available as they had during development. Jobs can be run on demand using Immediate jobs, or scheduled with a Cron expression using Scheduled Jobs. The integrated Job system can be used on its own, or it can be used to run code with tools like Airflow or Prefect.Screenshot of When deploying a project and publishing the results, Services help to deploy custom long-running programs like web servers to host results, or integrations can be used. From publishing processed data to S3 buckets, to hosting trained models on Nvidia Triton, to publishing dashboards in Apache Superset, it helps data scientists deploy their projects and their artifacts with minimal configuration or maintenance required