TrustRadius

Plotly Dash vs. Shiny

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Plotly Dash
Score 8.0 out of 10
N/A
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.N/A
Shiny
Score 8.0 out of 10
N/A
Shiny allows users to create data visualization apps, and is designed to be easy to write with. These apps let users interact with data and analyses with R or Python.N/A
Pricing
Plotly DashShiny
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Plotly DashShiny
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Plotly DashShiny
Considered Both Products
Plotly Dash
Verified User
Anonymous
Chose Plotly Dash
Tableau is great for basic dashboard visualisations using an ETL transfer layer from production. However, Plotly Dash is specifically designed for visualisation of machine learning applications. That's the key difference.
Shiny
Verified User
Anonymous
Chose Shiny
Whilst dashboarding may be comparable with some of the other products we evaluated. Nothing compared to the analytical capabilities on offer with Shiny. An added advantage was that we had colleagues knowledgeable in R which meant bringing in Shiny and getting to grips with it …
Kenton Woods | TrustRadius Reviewer
Kenton Woods
Research Assistant
Chose Shiny
Shiny is much cheaper to use than Tableau Desktop and Microsoft Power BI. It's not as fancy, and maybe not as effective, but you save lots of money by using Shiny over the previously listed alternatives. The graphs and charts you can make in Shiny are very good for …
Verified User
Anonymous
Chose Shiny
Both Tableau and Power BI are easier to learn and allow you to develop dashboards in a faster and more intuitive way, but both have limitations in what you can do with them and if you want to do something more specific it is always more complicated. RStudio is much more …
Verified User
Anonymous
Chose Shiny
- Faster response working with a large amount of data.
- R Studio connection and flexibility.
- Scenarios modelling.
VK
Varun Kumar
Data Science and Analytics Lead
Chose Shiny
Shiny can be a good tool in academic but its not upto standard of TMT industry but could possibly be useful in life science industry (which is where its more prevalent usually), its good as its mostly free (not including cost of servers and compute). I would rank its …
Verified User
Anonymous
Chose Shiny
Shiny allows easy and fast development of a product into production whereas Jupyter Notebook can be broken really easily by a user. The idea of having a specific server that works with that model is very practical and it's a good advantage.
In the contrary, the quantity of …
Features
Plotly DashShiny
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Plotly Dash
8.9
Ratings
6% above category average
Shiny
-
Ratings
Connect to Multiple Data Sources8.40 Ratings00 Ratings
Extend Existing Data Sources9.30 Ratings00 Ratings
Automatic Data Format Detection8.40 Ratings00 Ratings
MDM Integration9.50 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Plotly Dash
9.0
Ratings
6% above category average
Shiny
-
Ratings
Visualization9.00 Ratings00 Ratings
Interactive Data Analysis9.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Plotly Dash
6.2
Ratings
27% below category average
Shiny
-
Ratings
Interactive Data Cleaning and Enrichment4.40 Ratings00 Ratings
Data Transformations8.50 Ratings00 Ratings
Data Encryption3.90 Ratings00 Ratings
Built-in Processors8.00 Ratings00 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
Shiny
-
Ratings
Multiple Model Development Languages and Tools9.00 Ratings00 Ratings
Automated Machine Learning7.00 Ratings00 Ratings
Single platform for multiple model development9.00 Ratings00 Ratings
Self-Service Model Delivery8.50 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Plotly Dash
9.7
Ratings
13% above category average
Shiny
-
Ratings
Flexible Model Publishing Options9.50 Ratings00 Ratings
Security, Governance, and Cost Controls10.00 Ratings00 Ratings
Best Alternatives
Plotly DashShiny
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 8.6 out of 10
Supermetrics
Supermetrics
Score 9.7 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Supermetrics
Supermetrics
Score 9.7 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Plotly DashShiny
Likelihood to Recommend
8.0
(0 ratings)
8.0
(0 ratings)
User Testimonials
Plotly DashShiny
Likelihood to Recommend
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.
Verified User
Anonymous
Read full review
Shiny is very good for developing dashboards or web applications with specific functionalities. But it is not so easy to use to develop from scratch, it is always better to use another tool to have a general idea of ​​what is expected of a dashboard and then develop the most specific functionalities in Shiny. It is much more flexible than other tools and that is why I consider it to be better for most cases, only that it is more complex to develop or has a longer learning curve.
Verified User
Anonymous
Read full review
Pros
  • Simple codes to create quick graphs.
  • Nice exportable figures.
  • Good for the initial exploratory analysis of the data.
Verified User
Anonymous
Read full review
  • Data tables are appealing to look at.
  • Enables us to create trend indexes in an effective way.
  • Easy to integrate with the rest of my R syntax.
Kenton Woods | TrustRadius Reviewer
Kenton Woods
Research Assistant
Read full review
Cons
  • React JSX syntax support can be added/improved.
  • Built-in UI components can be improved.
  • The API used for AJAX calls can be made more understandable and simpler.
Verified User
Anonymous
Read full review
  • Shiny can be really time consuming to create visuals.
  • It needs excellent knowledge of R programming and coding skillset.
  • It still has a limited set of options to choose from.
VK
Varun Kumar
Data Science and Analytics Lead
Read full review
Alternatives Considered
Verified User
Anonymous
Read full review
Whilst dashboarding may be comparable with some of the other products we evaluated. Nothing compared to the analytical capabilities on offer with Shiny. An added advantage was that we had colleagues knowledgeable in R which meant bringing in Shiny and getting to grips with it was a lot more seamless and welcomed by the end users.
Verified User
Anonymous
Read full review
Return on Investment
  • Reduce product monetization lead time
  • Real time performance monitoring
  • Deep learning to allow better marketing segmentation models
Verified User
Anonymous
Read full review
  • We saw a good involvement to researchers when showing their models in shiny.
  • We can have a quicker review from the user when the model is in production.
  • False positives can be found easily and they help the retraining of the model.
Verified User
Anonymous
Read full review
ScreenShots