Plotly headquartered in Montreal creates data visualization and UI tools for ML, data science, engineering, and the sciences with language support for Python, R, Julia, and JS. Plotly's Dash aims to empower teams to build data science and ML apps that put Python, R, and Julia in the hands of business users. The vendor states that full stack apps that would typically require a front-end, backend, and dev ops team can be built and deployed in hours by data scientists with Dash.
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Saturn Cloud
Score 7.6 out of 10
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Saturn Cloud is an ML platform for individuals and teams, available on multiple clouds: AWS, Azure, GCP, and OCI. It provides access to computing resources with customizable amounts of memory and power, including GPUs and Dask distributed computing clusters, in a wholly hosted environment. Saturn Cloud is presented as flexible and straightforward for new data scientists while giving senior and experienced staff the
capabilities and configurability they need.…
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Pricing
Plotly Dash
Saturn Cloud
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Plotly Dash
Saturn Cloud
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Plotly Dash
Saturn Cloud
Features
Plotly Dash
Saturn Cloud
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Plotly Dash
8.9
Ratings
6% above category average
Saturn Cloud
-
Ratings
Connect to Multiple Data Sources
8.40 Ratings
00 Ratings
Extend Existing Data Sources
9.30 Ratings
00 Ratings
Automatic Data Format Detection
8.40 Ratings
00 Ratings
MDM Integration
9.50 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Plotly Dash
9.0
Ratings
7% above category average
Saturn Cloud
-
Ratings
Visualization
9.00 Ratings
00 Ratings
Interactive Data Analysis
9.00 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Plotly Dash
6.2
Ratings
27% below category average
Saturn Cloud
-
Ratings
Interactive Data Cleaning and Enrichment
4.40 Ratings
00 Ratings
Data Transformations
8.50 Ratings
00 Ratings
Data Encryption
3.90 Ratings
00 Ratings
Built-in Processors
8.00 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Plotly Dash
8.4
Ratings
0% above category average
Saturn Cloud
-
Ratings
Multiple Model Development Languages and Tools
9.00 Ratings
00 Ratings
Automated Machine Learning
7.00 Ratings
00 Ratings
Single platform for multiple model development
9.00 Ratings
00 Ratings
Self-Service Model Delivery
8.50 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Plotly Dash suits well where you need to build a web-based reporting tool as a minimum viable product. You will be surprised when you build your first hosted web-based reporting tool in a few minutes without the need for web development expertise. However, when it comes to building a more complete solution, you may feel a bit restricted by the options provided by the API. But as you imagine, this is the cost of the abstraction of the web development layer, in other words, simplicity vs completeness. Still, Plotly Dash is a powerful option whenever you prefer simplicity over completeness.
1. Large-scale data processing: If your organization needs to process vast amounts of data, Saturn Cloud's parallel computing capabilities make it an ideal choice for handling these tasks efficiently and quickly.
2. Complex machine learning projects: Saturn Cloud is beneficial when working on machine learning projects requiring scalable resources and powerful computational capabilities, such as training deep learning models or running complex algorithms.
3. Collaborative data science work: Saturn Cloud provides an excellent environment for data scientists and engineers to collaborate on projects, share resources, and maintain version control, ensuring consistency and smooth teamwork.
Less appropriate scenarios for Saturn Cloud: Small-scale projects: For smaller projects with limited data and less demanding computational requirements, Saturn Cloud's advanced features might not be necessary.
While Saturn Cloud offers a range of pre-built templates and workflows, there is currently limited support for customization. For example, users may not be able to modify the pre-configured environments that come with the templates, or may find it difficult to integrate their own custom libraries and tools. Offering more flexibility in this area could help users tailor the platform to their specific needs and workflows.
While Saturn Cloud offers a variety of pre-built environments for data science and machine learning workloads, some users may prefer to use custom Docker images instead. However, the platform currently has limited support for Docker, which can be a limitation for users who need to work with specific dependencies or custom libraries. Adding more robust support for Docker could help to make the platform more versatile and adaptable to a wider range of use cases.
This is user friendly , better than its counterparts. Anyone familiar working with other cloud solutions for GPU will agree on this. Hence the rating of 10 was given to this. I personally love the fact that I get so much compute time for being a free user which is very efficient in terms of budget
Saturn Cloud is an exceptional data science platform that offers a multitude of advantages to organizations. It excels in simplifying and optimizing data science workflows, providing scalable infrastructure resources, and promoting efficient collaboration among teams. With its user-friendly interface and seamless integration with popular tools, Saturn Cloud enhances productivity and accelerates the development of data science models. The platform's automation capabilities streamline repetitive tasks, freeing up valuable time for experimentation and analysis. Additionally, Saturn Cloud's cost-effective approach, with on-demand cloud resources, ensures efficient resource utilization and budget optimization. Its features for version control, reproducibility, and deployment management further solidify Saturn Cloud's position as a superior choice for organizations seeking to leverage the power of data science effectively.
Faster experimentation and model iteration: Saturn Cloud's scalability and user-friendly interface can help organizations to reduce the time required to set up and run experiments, as well as to iterate on models more quickly. This can help to speed up the development cycle and get products to market more quickly.
Increased productivity and efficiency: Saturn Cloud's built-in tools and pre-built environments can help to streamline data science workflows and reduce the time required to set up and configure environments. This can help data scientists to focus on higher-value tasks and improve overall productivity.