What is Shiny and what are its top alternatives?
Shiny is an R package that allows users to build interactive web applications directly from their R code. Key features of Shiny include the ability to create interactive dashboards, visualizations, and data exploration tools without needing to know web development languages like HTML, CSS, or JavaScript. However, limitations of Shiny include its dependence on R language and limited customization options for advanced users. 1. Dash by Plotly: Dash is a Python framework for building analytical web applications. Key features include interactive visualizations, declarative components, and easy-to-use syntax. Pros include support for both Python and R, while cons include a steeper learning curve compared to Shiny. 2. Bokeh: Bokeh is a Python library that provides interactive data visualization tools. Key features include interactivity, streaming and updating data, and real-time plotting. Pros include high-performance interactive visualizations, while cons include limited customization options. 3. Streamlit: Streamlit is a Python library for creating custom web apps for machine learning and data science projects. Key features include rapid prototyping, simple syntax, and easy deployment. Pros include fast development cycles, while cons include limited support for complex interactivity. 4. Dash Enterprise: Dash Enterprise is a commercial platform built on top of Dash for building and deploying analytical web applications. Key features include collaboration tools, secure deployment options, and advanced analytics capabilities. Pros include enterprise-grade support, while cons include cost considerations for commercial use. 5. Flexdashboard: Flexdashboard is an R package that enables users to create interactive dashboards using R Markdown. Key features include responsive layouts, integrated R code, and support for various data visualization libraries. Pros include seamless integration with R Markdown, while cons include limited customization options compared to Shiny. 6. Panel: Panel is a Python library for adding interactivity and widgets to existing plotting libraries. Key features include support for Bokeh, Matplotlib, and Plotly plots, as well as easy customization options. Pros include flexibility in combining different plotting libraries, while cons include a smaller community compared to Shiny. 7. RShinyProxy: RShinyProxy is an open-source platform for deploying and managing Shiny applications. Key features include scalability, user authentication, and integration with container platforms like Docker. Pros include easy deployment of Shiny apps, while cons include limited support for non-Shiny applications. 8. HoloViews: HoloViews is a Python library for building complex visualizations with a concise syntax. Key features include abstracting data from visualization details, support for multiple plotting libraries, and seamless integration with Panel. Pros include high-level declarative syntax, while cons include a learning curve for beginners. 9. Binder: Binder is a tool for creating custom computing environments from Jupyter notebooks. Key features include free hosting, support for interactive notebooks, and easy sharing of reproducible research. Pros include flexibility in creating custom environments, while cons include limitations in terms of scalability and resource usage. 10. AppRun: AppRun is a JavaScript library for building web apps with a reactive and component-based architecture. Key features include state management, routing, and server-side rendering. Pros include lightweight footprint, while cons include a lack of pre-built components compared to Shiny.
Top Alternatives to Shiny
- Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click. ...
- Dash
Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included. ...
- Plotly.js
It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more. ...
- Google Analytics
Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...
- Google Tag Manager
Tag Manager gives you the ability to add and update your own tags for conversion tracking, site analytics, remarketing, and more. There are nearly endless ways to track user behavior across your sites and apps, and the intuitive design lets you change tags whenever you want. ...
- Mixpanel
Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...
- Mixpanel
Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...
- Optimizely
Optimizely is the market leader in digital experience optimization, helping digital leaders and Fortune 100 companies alike optimize their digital products, commerce, and campaigns with a fully featured experimentation platform. ...
Shiny alternatives & related posts
- Capable of visualising billions of rows6
- Intuitive and easy to learn1
- Responsive1
- Very expensive for small companies3
related Tableau posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
Hello everyone,
My team and I are currently in the process of selecting a Business Intelligence (BI) tool for our actively developing company, which has over 500 employees. We are considering open-source options.
We are keen to connect with a Head of Analytics or BI Analytics professional who has extensive experience working with any of these systems and is willing to share their insights. Ideally, we would like to speak with someone from companies that have transitioned from proprietary BI tools (such as PowerBI, Qlik, or Tableau) to open-source BI tools, or vice versa.
If you have any contacts or recommendations for individuals we could reach out to regarding this matter, we would greatly appreciate it. Additionally, if you are personally willing to share your experiences, please feel free to reach out to me directly. Thank you!
- Dozens of API docs and Cheat-Sheets17
- Great for offline use12
- Works with Alfred8
- Excellent documentation8
- Quick API search8
- Fast5
- Good integration with Xcode and AppCode3
- Great for mobile dev work2
related Dash posts
- Bindings to popular languages like Python, Node, R, etc16
- Integrated zoom and filter-out tools in charts and maps10
- Great support for complex and multiple axes9
- Powerful out-of-the-box featureset8
- Beautiful visualizations6
- Active user base4
- Impressive support for webgl 3D charts4
- Charts are easy to share with a cloud account3
- Webgl chart types are extremely performant3
- Interactive charts2
- Easy to use online editor for creating plotly.js charts2
- Publication quality image export2
- Terrible document18
related Plotly.js posts
We use Plotly (just their open source stuff) for Zulip's user-facing and admin-facing statistics graphs because it's a reasonably well-designed JavaScript graphing library.
If you've tried using D3.js, it's a pretty poor developer experience, and that translates to spending a bunch of time getting the graphs one wants even for things that are conceptually pretty basic. Plotly isn't amazing (it's decent), but it's way better than than D3 unless you have very specialized needs.
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.
- Free1.5K
- Easy setup927
- Data visualization891
- Real-time stats698
- Comprehensive feature set406
- Goals tracking182
- Powerful funnel conversion reporting155
- Customizable reports139
- Custom events try83
- Elastic api53
- Updated regulary15
- Interactive Documentation8
- Google play4
- Walkman music video playlist3
- Industry Standard3
- Advanced ecommerce3
- Irina2
- Easy to integrate2
- Financial Management Challenges -2015h2
- Medium / Channel data split2
- Lifesaver2
- Confusing UX/UI11
- Super complex8
- Very hard to build out funnels6
- Poor web performance metrics4
- Very easy to confuse the user of the analytics3
- Time spent on page isn't accurate out of the box2
related Google Analytics posts
This is my stack in Application & Data
JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB
My Utilities Tools
Google Analytics Postman Elasticsearch
My Devops Tools
Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack
My Business Tools
Slack
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Google Tag Manager
related Google Tag Manager posts
Hi,
This is a question for best practice regarding Segment and Google Tag Manager. I would love to use Segment and GTM together when we need to implement a lot of additional tools, such as Amplitude, Appsfyler, or any other engagement tool since we can send event data without additional SDK implementation, etc.
So, my question is, if you use Segment and Google Tag Manager, how did you define what you will push through Segment and what will you push through Google Tag Manager? For example, when implementing a Facebook Pixel or any other 3rd party marketing tag?
From my point of view, implementing marketing pixels should stay in GTM because of the tag/trigger control.
If you are using Segment and GTM together, I would love to learn more about your best practice.
Thanks!
Mixpanel
- Great visualization ui144
- Easy integration108
- Great funnel funcionality78
- Free58
- A wide range of tools22
- Powerful Graph Search15
- Responsive Customer Support11
- Nice reporting2
- Messaging (notification, email) features are weak2
- Paid plans can get expensive2
- Limited dashboard capabilities1
related Mixpanel posts
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!
Mixpanel
- Great visualization ui144
- Easy integration108
- Great funnel funcionality78
- Free58
- A wide range of tools22
- Powerful Graph Search15
- Responsive Customer Support11
- Nice reporting2
- Messaging (notification, email) features are weak2
- Paid plans can get expensive2
- Limited dashboard capabilities1
related Mixpanel posts
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!
Optimizely
- Easy to setup, edit variants, & see results50
- Light weight20
- Best a/b testing solution16
- Integration with google analytics14
related Optimizely posts
Hey all, I'm managing the implementation of a customer data platform and headless CMS for a digital consumer content publisher. We're weighing up the pros and cons of implementing an OTB activation platform like Optimizely Recommendations or Dynamic Yield vs developing a bespoke solution for personalising content recommendations. Use Case is CDP will house customers and personas, and headless CMS will contain the individual content assets. The intermediary solution will activate data between the two for personalisation of news content feeds. I saw GCP has some potentially applicable personalisation solutions such as recommendations AI, which seem to be targeted at retail, but would probably be relevant to this use case for all intents and purposes. The CDP is Segment and the CMS is Contentstack. Has anyone implemented an activation platform or personalisation solution under similar circumstances? Any advice or direction would be appreciated! Thank you