

QlikView and Plotly Dash Enterprise compete in the business intelligence and analytics category. While QlikView has advantages in data handling, Plotly Dash Enterprise is more robust for customization and Python integration.
Features: QlikView is known for its robust data analysis and seamless integration with Salesforce, allowing real-time data access. It supports diverse data sources and complex analytics tasks, utilizing its associative model and in-memory technology for swift analysis. Plotly Dash Enterprise is favored for its integration with Python, enabling interactive dashboards with modular architecture. It excels in deployment ease, app hosting, and real-time data updates, providing advanced customization and collaboration tools.
Room for Improvement: QlikView users point out the need for better visual customization, more self-service features, and reduced costs, alongside improvements in natural language queries and visualization capabilities. Plotly Dash Enterprise could enhance its offerings with greater modularity, improved documentation, and additional chart options, paying attention to performance optimization for large data sets.
Ease of Deployment and Customer Service: QlikView's flexibility is reflected in its widespread on-premises deployments and hybrid setups, with strong reseller-based support and a helpful Qlik community. Plotly Dash Enterprise provides a mix of on-premises and cloud deployment, with efficient technical support praised for its responsiveness, allowing organizations to select suitable models.
Pricing and ROI: QlikView's pricing is considered steep, especially for small businesses, yet it presents strong ROI through time savings in data analysis. Plotly Dash Enterprise has varied pricing, viewed as costly but justified by its comprehensive features, yielding cost efficiencies and reduced development time through its enterprise solutions.
Ad-hoc analyses that used to take days have been reduced significantly, with one case where the team saved seven to ten days per month.
My team moved from a six-month dev cycle to two weeks.
Using Plotly Dash Enterprise built automated portals connected directly to localized storage saves time to insight—dropping it to under five minutes—and saves engineers hundreds of hours annually.
The biggest return on investment is the time saving for the customer.
They assist with installation, deployment, performance tuning, scalable architecture, and troubleshooting, which are valuable for initial setups and production-ready configurations.
Unlike many software companies where the first line of support is non-technical, Plotly splits it into two expert groups: Install Infra group and Solution group.
I have noticed specific outcomes from using Plotly Dash Enterprise.
I would rate the customer support a solid 10.
I am totally satisfied with technical support from Qlik.
We can scale by adding more instances to handle multiple users efficiently, with the ability to support hundreds to thousands of users with proper backend performance control.
For infrastructure scalability, we are thinking about Docker or Kubernetes while also utilizing Redis for a shared state, making auto-scaling based on CPU or RAM usage available.
Plotly Dash Enterprise provides a strong foundation for scalability, but the real performance comes from combining the platform with a good design system.
If you want better performance with a larger volume of data, you can simply add an additional server.
It allows us to build, design, and deploy production-grade applications independently in Python.
Plotly Dash Enterprise is stable.
Plotly Dash Enterprise is stable in my experience, being reliable for implementation and deployment to production.
A more guided user interface and low-code features would help with onboarding for beginners and non-technical users, making the platform more accessible.
There should be a focus on mobile responsiveness and shifting from standard CSS to Dash Mantine Components and Dash Bootstrap while utilizing grid systems for large data bottlenecks.
I wish for features such as auto detection of data and auto analysis to be included.
In QlikView, I believe the improvement that should be made is to bring the costs down, as you'll have to be competitive with Power BI, aiming for at least a 30% reduction to stop the hemorrhaging to Power BI.
It would be beneficial to have AI or ML features in QlikView.
The cost can be significant, such as tens of thousands per year, but it includes features such as security, deployment, and support, which justifies it for a larger team.
The enterprise price can reach around one hundred thousand dollars per year, varying according to organizational size.
The setup cost was nothing and is fine.
The license cost per user or per year for QlikView is about 500 Euros annually.
I would rate the pricing for QlikView as not cheap, but it is reasonable.
The built-in handling of Kubernetes and Docker in Plotly Dash Enterprise makes our workflow easier because we only need to configure the dashboard once on how the data should look.
The control access feature helps my team by using authentication code, so we can ensure only the people who should have access can view the dashboard.
The centralized data platform holds dashboards and supports version control and app management, along with interactive capabilities such as KPIs and data pipelines connecting databases, ETL systems, and ML models, fitting well into modern data stacks.
The best features in QlikView are rapid development, the fact that I can do what I want in QlikView, and full control along with ease of use.
Building metrics using simple language, similar to what you have in Excel, is what I have found most valuable in QlikView.
| Product | Mindshare (%) |
|---|---|
| Plotly Dash Enterprise | 1.6% |
| QlikView | 3.9% |
| Other | 94.5% |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 4 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 73 |
| Midsize Enterprise | 36 |
| Large Enterprise | 76 |
Plotly Dash Enterprise is a commercial platform designed for creating and deploying data visualization applications. It provides advanced tools and infrastructure to simplify the process of building interactive dashboards and analytics applications.
Plotly Dash Enterprise enables professionals to harness the power of Dash framework for enterprise-level scalability and deployment. By integrating seamlessly with existing workflows, it supports easy collaboration while ensuring robust data security. Users appreciate its ability to streamline the development of sophisticated visualizations that can be customized to meet specific analytical needs.
What are the standout features?Plotly Dash Enterprise is employed in finance for real-time analytics dashboards, in healthcare for patient data visualization, and in marketing for customer insights. Its adaptability and ease of integration make it suitable across diverse industry applications where visual data analysis is critical.
QlikView enhances data analysis with its associative data model and rapid in-memory processing, providing dynamic dashboards and robust visualization, while efficient data integration allows connections to multiple sources.
QlikView offers powerful analytics and insight generation capabilities through its integration with Salesforce, enabling real-time sales data access. Its customizable dashboards are complemented by scripting for complex calculations and QVDs for performance optimization. Designed to be user-friendly, it supports ETL processes and diverse data browsing, allowing users to interact with data intuitively. However, there is room for improving licensing complexities, scalability, and self-service functionality. Additional enhancements are desired in visualization, integration with Qlik Sense, and predictive analytics support.
What are QlikView's key features?QlikView finds use in building business intelligence dashboards across sectors, integrating with Salesforce for analytics, supporting financial planning, and tracking sales. Its intuitive interface aids manufacturing companies in KPI monitoring and informs commercial decisions. The tool enhances reporting, ETL processes, and diverse data source integration, facilitating offline data access.
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