Qlik Sense and Apache Superset are data analytics tools competing in the business intelligence category. Users find Apache Superset superior due to its feature set and perceived value.
Features: Qlik Sense offers enhanced data profiling, powerful data prep, and rapid application development. Apache Superset is known for its intuitive KPI-building capabilities, flexible dashboard customization, and no-code interface.
Room for Improvement: Qlik Sense needs improvements in data integration, real-time analytics, and reducing reliance on proprietary file formats. Apache Superset could enhance interactivity and user permissions management, and offer more customization options.
Ease of Deployment and Customer Service: Qlik Sense supports multiple deployment options, catering to various organizational needs. Apache Superset is cloud-based, appealing to those preferring less complex setups. Both have positive user communities, with Apache Superset's community support being notably vibrant.
Pricing and ROI: Apache Superset’s open-source nature offers a cost-effective solution, making it appealing for budget-conscious organizations. Qlik Sense, while offering rapid ROI through time savings and improved decision-making, can be pricey due to substantial licensing costs.
| Product | Mindshare (%) |
|---|---|
| Apache Superset | 2.5% |
| Qlik Sense | 4.7% |
| Other | 92.8% |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 2 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 34 |
| Midsize Enterprise | 40 |
| Large Enterprise | 89 |
Apache Superset provides seamless integration for data visualization and dashboard creation without the need for developer assistance. Its intuitive, no-code environment supports users to embed, query, and share data insights efficiently.
Apache Superset offers a robust platform for data visualization through easy dashboard configuration and data integration. It facilitates query writing and reuses KPIs to ensure data consistency across dashboards. Users can embed dashboards within applications effortlessly and leverage a wide range of chart options for sophisticated data representation. The self-service nature empowers teams to maintain data integrity and optimize processes swiftly. However, it seeks enhancement in documentation and dynamic dashboard navigation, with a need for more interactive features to rival industry-leading tools. Permissions management and interactivity need enhancement, especially in larger user environments.
What are the key features of Apache Superset?Industries utilize Apache Superset to create and integrate dashboards for data analysis and visualization. It is widely used in genomics to analyze data, monitor service performance in telecom, and manage metrics and KPIs. Companies leverage its capabilities for profitability insights, agent productivity assessments, and historical data trend analysis.
Qlik Sense offers drag-and-drop dashboard creation, multi-data source integration, and self-service analytics. Users benefit from associative data modeling and real-time insights. The platform enhances quick deployment across any device with its flexibility and ease of use.
Qlik Sense provides rapid dashboard creation and seamless multi-data source integration, supporting real-time analytics and high-speed ETL capabilities. Users enjoy advanced visualizations and natural language processing within an intuitive interface. The solution's in-memory engine ensures fast data processing while offering flexibility and quick deployment on all devices. Its open API facilitates extensive customization and integration with chatbots and third-party extensions.
What are the key features of Qlik Sense?In industries such as finance and sales, Qlik Sense enables interactive data analyses and dashboard creation across departments. It supports business intelligence for financial reporting, sales analysis, and decision-making. By automating reporting and combining data from multiple sources, it facilitates users in generating insights and enhancing data accessibility for informed business decisions.
We monitor all Data Visualization reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
