StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Utilities
  3. Business Intelligence
  4. Business Intelligence
  5. Qlik Sense vs Superset

Qlik Sense vs Superset

OverviewComparisonAlternatives

Overview

Superset
Superset
Stacks420
Followers1.0K
Votes45
Qlik Sense
Qlik Sense
Stacks122
Followers100
Votes0

Qlik Sense vs Superset: What are the differences?

Qlik Sense and Superset are two popular data visualization and analytics tools that offer different features and capabilities. Below are the key differences between Qlik Sense and Superset:

  1. Data Source Connectivity: Qlik Sense provides a wide range of data source connectors, allowing users to seamlessly integrate and visualize data from various sources such as databases, cloud services, and file systems. In contrast, Superset primarily supports SQL-based data sources, limiting the connectivity options for users.

  2. Visualizations and Dashboarding: Qlik Sense offers a rich set of visualization options, including charts, graphs, and maps, with interactive features that enable users to explore and analyze data in real-time. Superset also provides various visualization options, but its focus is more on creating interactive dashboards using SQL queries and predefined charts.

  3. User Interface and Ease of Use: Qlik Sense prioritizes user-friendly interfaces and provides drag-and-drop functionalities, making it easier for users to create visualizations and build analytics workflows without deep technical knowledge. Superset, on the other hand, requires users to have some SQL proficiency and provides a less intuitive user interface compared to Qlik Sense.

  4. Collaboration and Sharing: Qlik Sense puts emphasis on collaboration and allows users to share their visualizations and dashboards with others, enabling collaborative data exploration and decision making. While Superset supports sharing of dashboards, it lacks some advanced collaboration features available in Qlik Sense, such as shared bookmarks and commenting capabilities.

  5. Enterprise Features: Qlik Sense provides robust enterprise features like data governance, security, and scalability, making it suitable for large organizations with complex data environments. Superset, on the contrary, lacks comprehensive enterprise-grade features and may require additional tools or manual configuration to meet enterprise requirements.

  6. Pricing and Licensing: Qlik Sense follows a commercial licensing model, where users need to purchase licenses based on their usage and requirements. Superset, on the other hand, is an open-source tool released under the Apache License, making it freely available for use, but may require additional setup and maintenance resources.

In summary, Qlik Sense offers a wide range of data connectors, intuitive interface, collaboration capabilities, and robust enterprise features, making it a suitable choice for organizations that require powerful and user-friendly data visualization and analytics. On the other hand, Superset focuses more on SQL-based data sources, interactive dashboards, and being an open-source tool, making it a viable option for users with SQL expertise and budget constraints.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Superset
Superset
Qlik Sense
Qlik Sense

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

It helps uncover insights that query-based BI tools simply miss. Our one-of-a-kind Associative Engine brings together all your data so users can freely search and explore to find new connections. AI and cognitive capabilities offer insight suggestions, automation and conversational interaction.

A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities;An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler);A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user;Deep integration with Druid allows for Caravel to stay blazing fast while slicing and dicing large, realtime datasets;
-
Statistics
Stacks
420
Stacks
122
Followers
1.0K
Followers
100
Votes
45
Votes
0
Pros & Cons
Pros
  • 13
    Awesome interactive filtering
  • 9
    Free
  • 6
    Wide SQL database support
  • 6
    Shareable & editable dashboards
  • 5
    Great for data collaborating on data exploration
Cons
  • 4
    Link diff db together "Data Modeling "
  • 3
    It is difficult to install on the server
  • 3
    Ugly GUI
No community feedback yet

What are some alternatives to Superset, Qlik Sense?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Periscope

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

Related Comparisons

Postman
Swagger UI

Postman vs Swagger UI

Mapbox
Google Maps

Google Maps vs Mapbox

Mapbox
Leaflet

Leaflet vs Mapbox vs OpenLayers

Twilio SendGrid
Mailgun

Mailgun vs Mandrill vs SendGrid

Runscope
Postman

Paw vs Postman vs Runscope