Apache Superset vs Tableau
Tableau is one of the most popular data integration and data visualization tools. The company originally started as a project of the Computer Science department at Stanford University. Tableau started life as a desktop application for Windows, but has now expanded to the web as well.
Tableau Desktop used to be a pioneer in the business intelligence field, popularizing concepts like lineage and no-code chart building.
Over time, Tableau grew in features to become the “Photoshop” of data visualization, but with it also higher complexity, price, and difficulty managing & scaling the tool. However, in 2019, Salesforce acquired Tableau and massively slowed down product development. Naturally, the question we ask ourselves is how relevant is Tableau today when the data ecosystem has become cloud-native, web-first, and centered around open source primarily?
Tableau is still a popular tool amongst existing organizations that have adopted Tableau. However, Tableau is falling prey to the Innovator’s Dilemma as newer organizations (even large ones) are choosing not to adopt Tableau so readily.
To understand why, let’s compare how fast moving data teams would like to work with what Tableau offers:
|Fast Moving Data Teams||Where Tableau Falls Short|
|Time to Sharing Analytics Assets||Links and invitations to the work shared in Slack or Email. Collaborators can view and interact in seconds||Prohibitively expensive pricing, a desktop first approach, slow load times. Minutes to hours to overcome|
|Integration with the Modern Data Stack||Proper change management (version control or assets as code) and tight integration with software development lifecycle||Tableau lives purely at the end of the data workflow as an island. Assets can’t be version controlled and change management is complex (broken dashboards are common)|
Apache Superset is an open source business intelligence platform that’s accessible for both business users as well as heavy SQL users. Superset is the most popular (by Github stars) open source business intelligence platform.
Out of the box, Superset supports over 60 chart types and over 40 of the most popular databases.
Because Apache Superset is an open source tool, you can also extend the functionality of Superset to support more databases, charts, custom roles and permissions, and so much more.
Apache Superset As a Tableau Alternative
Max Beauchemin originally created Apache Superset at Airbnb to serve as an alternative to Tableau. His team was struggling to scale the performance of and access to Tableau internally. At the time, Tableau couldn’t natively connect to Druid or Presto, their preferred data engines. Tableau’s Live Mode was also misbehaving when we pointed it to our traditional databases and they were encouraged to use Extracts. Tableau extracts couldn’t handle the data volumes that Max’s team was handling.
More importantly, the cost of individual Tableau licenses and the desktop centric approach didn’t scale to the thousands of users within Airbnb. You can read more about the limitations of Tableau that Max’s team ran into here.
Supported Data Sources
Both Apache Superset and Tableau support a large number of data sources, but Tableau falls short when it comes to building custom database drivers.
|SQL Databases||High quality support for popular SQL databases||High quality support for popular SQL databases|
|NoSQL Databases||Native support for MongoDB, etc||Using Trino or Presto|
|Custom database drivers||Limited support (using ODBC)||High quality support for building first class database connectors|
Both Apache Superset and Tableau provide a large gallery of visualizations out of the box and both provide the ability for the addition of new chart types.
|Simple chart types (bar, pie, big number, etc)||✅ Rich support||✅ Rich support|
|Time Series charts|