Sold by: Plotly
Deployed on AWS
Plotly Dash is a data application platform for building scalable, interactive Python data apps for production, used by global data science and analyst teams.
4.2
Overview
Dash Enterprise puts data and AI into action with the creation of production-grade data apps for your business. Python is the premier language of AI and data and Dash Enterprise is the leading vehicle for delivering Python-based, interactive insights and analytics to business users. The pricing in this listing reflects the base rate for Dash Enterprise with the below specifications. For private offers and other configurations, please contact Plotly at info@plotly.com .
Highlights
- Dynamic: Build sophisticated interactivity into your data apps, write back data, and create beautiful, shareable insights.
- Flexible: Customize every pixel of your data app easily, without a line of front end code. Focus on Python analytics without compromising app look-and-feel or branding.
- Production-grade: Enjoy advanced security features for data insights at scale. Reduce IT dependence with one-click deployment, automated CI/CD, embeddable data apps, and more.
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Trust Center
Access real-time vendor security and compliance information through their Trust Center powered by Drata or Vanta. Review certifications and security standards before purchase.
Buyer guide
Gain valuable insights from real users who purchased this product, powered by PeerSpot.
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Custom | Dash Enterprise software | $50,000.00 |
Vendor refund policy
No refunds.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
First Release
Additional details
Usage instructions
Product setup, configuration, and access instructions are available in detail here: https://dash.plotly.com/dash-enterprise/install-cloud-marketplace
Resources
Vendor resources
Support
Vendor support
Email support issues for Enterprise customers are triaged immediately, with escalation and further investigation when required. After initial discussions, you can follow up by requesting a screen-share meeting for enhanced support. Our solutions support hours are between 4am to 6pm ET, Monday to Friday. Please contact info@plotly.com for support.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Plotly
By Luzmo
By MicroStrategy, Inc.
Top
100
In Analytic Platforms
Top
50
In Financial Services, Business Intelligence & Advanced Analytics
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Interactive Data Visualization
Build sophisticated interactivity into data apps with dynamic user interfaces and shareable insights
Python-Based Application Development
Create production-grade data applications using Python as the primary programming language for analytics and AI workflows
Customizable User Interface
Customize visual elements and styling without requiring front-end code, maintaining application branding and appearance
Advanced Security Features
Implement advanced security mechanisms for protecting data insights and analytics at scale
Automated Deployment and CI/CD
Enable one-click deployment with automated continuous integration and continuous deployment pipelines for data applications
Whitelabel and Customization Capabilities
Whitelabel analytics options enabling seamless in-product experience with personalized dashboards and analytics tailored to client-specific needs without code modifications.
Self-Service Analytics and User Empowerment
Self-service analytics allowing end-users to create their own insights through Studio and Modular Report Builder with exploration and editing capabilities.
Data Connectivity and Integration
Library of pre-built database connectors, applications, and services accessible via APIs for seamless data connection and integration.
Security and Access Control
Secure embedding with Single Sign-On (SSO), role-based access control (RBAC), and multitenant analytics support for secure data isolation.
AI-Powered Insights and Natural Language Processing
Built-in AI capabilities including Agent APIs for generating analytics conversation summaries, natural language dataset discovery, and automatic description generation for new datasets and columns.
Universal Semantic Layer
Centralized repository for business definitions, hierarchies, and security rules that ensures consistent metrics and KPIs across all tools and users.
Native Data Connectors
Support for 200+ native data connectors enabling live connection to multiple data sources and delivery of reusable data across BI tools, AI agents, and workspaces.
Real-time Governance and Monitoring
Integrated Sentinel layer providing proactive, real-time monitoring for data breaches, compliance risks, and cost-saving opportunities with immediate intelligence and alerts.
Policy-Driven Access Controls
Protection of enterprise data through policy-driven access controls, live monitoring, and isolation mechanisms to ensure users only access authorized data.
AI Agent Integration
Support for enterprise AI agents that access governed, trusted metrics across systems to deliver accurate business-aware answers and enable confident decision-making at scale.
Standard contract
No
No
No
Customer reviews
Mohamed-Trabelsi
Building interactive dashboards has improved reporting and supports better operational decisions
Reviewed on Jun 01, 2026
Review provided by PeerSpot
What is our primary use case?
My full name is Muhammad Trabelsi. I currently work as a Logistics and Administrations Associate at the IT Center , an international NGO based in Geneva, Switzerland. In addition to my operational and logistics responsibilities, I have recently developed a strong interest in data science and data visualization. I use Python for data analysis and have worked with libraries such as Plotly Dash, Pandas, and Plotly Express to create interactive dashboards and analytics tools.
What is most valuable?
I have mainly worked with the open-source Dash ecosystem, and my experience has been very positive. It has shown me how quickly data can be transformed into interactive and useful applications. I would be interested in learning more about Plotly Dash Enterprise , especially its collaboration, deployment, and security. In an international organization like ours, where data reporting and operational efficiency are important, I can see potential value in exploring enterprise-grade solutions if they can help teams develop and maintain applications more efficiently.
What needs improvement?
My organization does not have any business relationship with Plotly beyond being a user of the open-source tools. We are not a Plotly partner, reseller, or service provider.
I have not used Plotly Dash Enterprise yet. My experience has been with the open-source Plotly and Dash frameworks for building interactive dashboards and data visualization applications.
I am mainly working with the open-source Plotly and Dash tools. I have not had direct exposure to Plotly Dash Enterprise through my organization, but I have built several dashboards and web applications using the open-source ecosystem.
For how long have I used the solution?
I have worked in logistics and administration for this NGO for over nine years, and I have been using Python, Plotly, and Dash for about a year to build dashboards and data visualization projects.
What other advice do I have?
I think my advice would be to start with the open-source Dash tools first. Build small dashboards, understand callbacks, layouts, and deployment basics. Once your dashboards become critical for teams, security, scaling, and collaboration, then Plotly Dash Enterprise can be a strong option. The most important thing is to focus on the user need, not only the technology. A simple, clear dashboard is often more valuable than a complex one.
My advice would be to start by clearly identifying the business problem you want to solve. Plotly Dash is most valuable when it helps users make decisions, not only display data, and that is what I discovered with the open-source solution. If you are already building dashboards with the open-source version and need stronger collaboration, governance, and security, then Plotly Dash Enterprise is worth exploring. I would also recommend starting with a pilot project involving end users early and measuring the impact on productivity and decision-making before scaling adoption across the organization.
Mohamed-Trabelsi
Building interactive dashboards has improved operational decisions in an international NGO
Reviewed on Jun 01, 2026
Review provided by PeerSpot
What is our primary use case?
My name is Mohamed Trabelsi, and I currently work as a logistics and administration associate at the AT Center, an international NGO based in Geneva, Switzerland. In addition to my operational and logistics responsibilities, I have recently developed a strong interest in data science and data visualization. I use Python for data analysis and have worked with libraries such as Plotly Dash, Pandas, and Plotly Express to create interactive dashboards and analytics tools.
I have worked in logistics and administration for this NGO for over eight or nine years, and I have been using Python, Plotly, and Dash for about a year to build dashboards and data visualization projects.
I have not used Plotly Dash Enterprise yet. My experience has been with the open-source Plotly and Dash frameworks for building interactive dashboards and data visualization applications.
I am mainly working with the open-source Plotly and Dash tools. I have not had direct exposure to Plotly Dash Enterprise through my organization, but I have built several dashboards and web applications using the open-source ecosystem.
What is most valuable?
I have mainly worked with the open-source Dash ecosystem, and my experience has been very positive. It has shown me how quickly data can be transformed into interactive and useful applications. I would be interested in learning more about Plotly Dash Enterprise, especially its collaboration, deployment, and security features. In an international organization like ours where data reporting and operational efficiency are important, I can see potential value in exploring enterprise-grade solutions if they can help teams develop and maintain applications more efficiently.
What other advice do I have?
I think my advice would be to start with the open-source Dash tools first. Build small dashboards, understand callbacks, layouts, and deployment basics. Once your dashboards become critical for teams, security, scaling, and collaboration, then Plotly Dash Enterprise can be a strong option.
The most important thing is to focus on the user need, not only the technology. A simple, clear dashboard is often more valuable than a complex one.
My advice would be to start by clearly identifying the business problem you want to solve. Plotly Dash is most valuable when it helps users make decisions, not just display data, and that is what I discovered with the open-source solution. If you are already building dashboards with the open-source version and you need stronger collaboration, governance, and security, then Plotly Dash Enterprise is worth exploring. I would also recommend starting with a pilot project involving end users early and measuring the impact on productivity and decision-making before scaling adoption across the organization. I would rate this review as highly positive based on my experience with the open-source tools.
Zakaria Zakaria
Interactive dashboards have transformed survey analytics and now support real-time decision-making
Reviewed on Jun 01, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Plotly Dash Enterprise is for data analytics, especially where we are involved in the analytics and visualization for better decision-making.
What is most valuable?
When I use Plotly Dash Enterprise day-to-day, it typically starts with building interactive dashboards and analytics applications using Python without requiring any heavy front-end development. Being in a market research company, our team uses it to turn raw survey or business data into live visual dashboards that help clients and our teams to monitor insights in real time, leading to better decision-making.
What needs improvement?
For some of my colleagues, especially those coming from market research operations, the transition to Plotly Dash Enterprise needed more structured training because they heavily depended on Excel manual reporting and static PowerPoints before using Plotly Dash Enterprise. Their main challenges were understanding the live dashboards; I have no problem with this because I have used Power BI, but it was a problem for them to understand live dashboards instead of static files, interpreting interactive charts, using filters correctly, and trusting automated data uploads rather than manually checking everything. Fifty members from operations needed to adapt to real-time KPI monitoring, recruiters' performance tracking, and automated quota management.
For how long have I used the solution?
I have been familiar with Plotly Dash Enterprise for about two and a half years.
How was the initial setup?
When we implemented Plotly Dash Enterprise, the timeline for getting everything up and running depends on the complexity of data, the needs for automation, and the scope of the dashboard. The typical timeline is around two to five days for simple charts, just survey tracking, and for Excel or CSV file uploads and some basic filters. However, for a professional internal dashboard, it might take around one to three weeks or one to five weeks. If we require a full operational enterprise system, it can take up to three months, including aspects such as cloud deployment, role-based access, machine learning integration, scalability, multiple pipelines, live APIs, and quality checks.
What other advice do I have?
Adoption of Plotly Dash Enterprise across my organization is not limited to just one person or a small task; it is commonly used across multiple departments, but the way it is used can differ depending on each team's needs.
For example, when I work with the US team from my country, we have operations, business development, sales, and HR. The Operations team may use it for survey tracking, recruiter performance, and fieldwork status, while management may use it for KPIs, revenue trends, and project progress. As research analyst teams, we use it for predictive modeling, quality control, fraud detection, and advanced visual analytics. Client servicing teams, such as business development, may use client-facing dashboards to share live insights and reports with the end clients.
My background was mostly beneficial as Plotly Dash Enterprise is Python-based and relatively intuitive for me since I already work with data analysis tools such as Pandas and SQL, but most of my colleagues were not in the same situation. I would rate this product highly based on its capabilities and impact on our organization.
Shail Shukla
Rapid deployments have accelerated analytics delivery and simplified real-time user updates
Reviewed on Jun 01, 2026
Review from a verified AWS customer
What is our primary use case?
I have been building analytics web applications and deploying those applications on Plotly Dash Enterprise . All of the apps are built locally in generic code IDEs like Visual Studio Code , and then the changes are deployed on Plotly Dash Enterprise server. I believe it is deployed on a private cloud.
What is most valuable?
One of the best features of Plotly Dash Enterprise is the simplicity of deploying changes. Deployment is generally a part where most developers are concerned when it does not remain local or specific to a group of developers but becomes open to all users. Plotly Dash Enterprise has made this process very easy. It is just a Git push command, and then your app goes live to all users who have access to that server. That is one of the most interesting and fascinating features.
The UI for Plotly Dash Enterprise is very intuitive, where even someone who has just started using Plotly Dash Enterprise can come and tweak their changes and configure all these things, whether it be user access management, analytics that they want to run on the deployed apps, or any other services that they have. It is all very easy to configure, very easy to tune, and easy to get started with. The simplicity and the way it works makes it very intuitive and straightforward, even if you have just started working on it.
Earlier, the entire code was deployed on their own server. Since the entire development and the front end is now powered by Plotly Dash Enterprise, it was a very good decision to switch to Plotly Dash Enterprise server itself so that it can scale natively and be deployed very easily from development to deployment. The time of deployment has been reduced significantly. I can develop a feature and have that feature live in approximately five minutes. That is the most important thing an organization looks for. Changes are getting through and users are able to see the changes almost in real time, within five or ten minutes.
This has impacted operations significantly. In cases where there have been failures, minor bugs, or dependency issues between the modules or packages that we use, even if a production level application has issues, I can directly jump in, fix the code, and have the entire production level system updated in approximately five minutes. The changes are reflected transparently and conveniently for developers because we are putting in our efforts to make sure that all releases go well. Plotly Dash Enterprise makes it very transparent for users to actually see the changes and the effort involved. Even if something is wrong, we know and we trust the system that once we fix this, it will be there in approximately five minutes. That is something that really encourages developers to be more proactive about finding bugs, troubleshooting things, and coming up with better features.
What needs improvement?
There are a couple of things I feel could be improved. With the new version, I feel that there is an opportunity to log, download the logs, and export the logs. I have seen that in one of my environments where it has already been upgraded to the new version. The logging, exporting the logs, or looking at the logs is putting a lot of things into the logs, and then most of the things are just about component updates or something very generic, which has nothing to do with developers. Developers would look into the logs only when a specific condition arises, something breaks, or during troubleshooting exercises. This could be simplified, the way Plotly Dash Enterprise logs everything. It should be exportable, and any simplification that can be done on the log side would be very useful.
I feel documentation and integration are pretty easy, so I would not comment much on that. Logs are something we have really invested our efforts in, and we have come up with some custom solutions as well, such as manually logging things into the database, like which user has just logged in and where they visited. If that comes natively with Plotly Dash Enterprise, it would be very easy for the app level analytics and user experience. The way we capture the logs, the way we can save and revisit the logs is something that can be simplified and improved.
For how long have I used the solution?
I have been using Plotly and deploying the apps directly on Plotly Dash Enterprise for roughly three to 3.5 years.
What other advice do I have?
I chose a rating of eight because it is overall a very great tool for someone who is building very specific use cases or data-driven web applications or some kind of specific analytics. It is very easy to host it, deploy it, and make it available for a large number of users with some simple tweaks and configurations. If your application is ready and you are just getting started with Plotly Dash Enterprise server, it would hardly take around 30 minutes to an hour to have it live, deployed, and ready for your users to work with. However, eight is given because there is still some room for improvement, and that keeps you proactive about always improving and always needing to hear the clients' or customers' feedback.
I would say you should definitely try Plotly Dash Enterprise. If you know Python, if you know Plotly, and you are already working with very simple or specific web applications that require you to work with Plotly and Dash, I think it would be perfect. Plotly and Dash as an enterprise have invested and improved the way the components are built and scaled. I have been using it for almost four years now and have seen how it has grown from the beginning. It can definitely work as a full-fledged web application. Earlier it was very specific to some data-driven analytics or insights, but now it can also be used for some web applications. I have seen how far it can go and how we can scale it with a massive amount of data. One should definitely get started if you know the basics of Plotly and can come up with a very simple UI. Try to put something out there for people rather than building things locally that run only for you. Try to make something simple, but that everyone has access to. Deployment is a big part, and often people forget about this part or do not even try to care about it, but that really differentiates someone who is building it for examples or practices from someone who is genuinely trying to build something for people. My overall review rating for Plotly Dash Enterprise is eight out of ten.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Hugo Souza Almeida
Data dashboards have transformed how I analyze COVID impacts across healthcare categories
Reviewed on May 31, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Plotly Dash Enterprise was working in health tech, where I deployed and created dashboards for internal clients.
A specific example of a dashboard I built for my internal clients is a COVID study that downloaded Brazilian government healthcare data. I analyzed quality of care, internment time, and costs for hospital time for patients across all International Classification of Disease categories. The conclusion was that COVID increased mortality rate and internment time across all International Classification of Disease categories, not just COVID.
I also developed a COVID prediction app and a few others, but the COVID study was the main use case for Plotly Dash Enterprise .
What is most valuable?
Plotly Dash Enterprise offers practical features that integrate visually appealing Plotly dashboards with Dash. The dashboards are easy to use and deploy.
Plotly Dash Enterprise has positively impacted my organization by enabling a small team of developers to deploy numerous dashboards with ease. Customization is straightforward with Plotly Dash Enterprise, and the user experience delivers high satisfaction. I was able to create login fields that allow clients to access their own segregated data.
What needs improvement?
Plotly Dash Enterprise is already quite good in terms of areas for improvement.
For how long have I used the solution?
I have been using Plotly Dash Enterprise for a year and a half.
What do I think about the stability of the solution?
Plotly Dash Enterprise is stable.
What do I think about the scalability of the solution?
Plotly Dash Enterprise's scalability is quite good.
How are customer service and support?
Plotly Dash Enterprise's customer support is quite good, but I did not need to use it because the application was well-developed.
Which solution did I use previously and why did I switch?
I only used Plotly Dash Enterprise and did not previously use a different solution.
How was the initial setup?
My experience with pricing, setup cost, and licensing for Plotly Dash Enterprise was mostly indirect, but from what I could observe, it was quite good.
What about the implementation team?
Before choosing Plotly Dash Enterprise, I was not a tech lead. The tech lead strongly preferred Plotly Dash Enterprise and recommended that I use it.
What was our ROI?
As a single developer, I was able to complete the COVID study independently as an intern, which demonstrates the impact on productivity and time saved.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing for Plotly Dash Enterprise was mostly indirect, but from what I could observe, it was quite good.
Which other solutions did I evaluate?
Before choosing Plotly Dash Enterprise, I was not a tech lead. The tech lead strongly preferred Plotly Dash Enterprise and recommended that I use it.
What other advice do I have?
Plotly Dash Enterprise's governance and security are quite good. Regarding Plotly Dash Enterprise's AI capabilities, the accuracy and reliability of output are strong. I would recommend that others definitely use Plotly Dash Enterprise. I give this product a rating of 10.