Apache Superset vs Tableau: 4 Critical Differences

on Apache Superset, BI Tool, Data Driven, Data Driven Strategies, Tableau • June 7th, 2021 • Write for Hevo

Apache Superset and Tableau are Business Intelligence tools used by organizations to visualize and gain insight from their data. Apache Superset is an open-source cloud-native application that can handle data at the petabyte scale. Tableau is known in the community as a leader in Analytics with a platform that is easy to use and offers countless integrations.

This article will give you an idea about Apache Superset vs Tableau on 4 different fronts namely platform features, flexibility, supported data sources, authorization, authentication, and pricing.

Table of Contents

Introduction to Apache Superset

Apache Superset vs Tableau: Apache Superset logo
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Apache Superset is a lightweight open-source business intelligence web application. It started as a hackathon project by Maxime Beauchemin while he was at Airbnb and was later adopted into the apache incubator program in 2017. It graduated from being an incubator program to a top-level project at Apache Software Foundation.

Apache Superset is used for data exploration and visualization. It provides a wide range of options to visualize your data from pie charts to highly detailed geospatial charts.

Features of Apache Superset

  • It provides a rich set of visualizations to represent your data on a dashboard.
  • Apache Superset allows you to build custom visualizations with its visualization plug-in architecture, allowing you to extend its capabilities.
  • Apache Superset supports most SQL-based databases through SQLAlchemy. This allows integration to MySQL, PostgreSQL, Oracle, Microsoft SQL Server, Redshift, MariaDB, SQLite, and lots more.
  • Apache Superset can also be integrated with Apache Druid. Apache Druid is a database used in applications to handle fast query performance, real-time responses, and high uptimes are paramount.
  • Apache Superset allows you to execute SQL queries in the SQL tab(a built-in SQL IDE) to explore your data. 
  • Apache Superset uses an extensible security model to determine access to its features and integrates with major authentication providers (OAuth, OpenID, LDAP, etc).

Introduction to Tableau

Tableau logo
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Tableau is a Data Visualization software used in business intelligence founded in 2003 by 3 Stanford students – Christian Chabot, Pat Hanrahan, and Chris Stolte. They started by specializing in visualization techniques for exploring and analyzing relational databases and data cubes – a multi-dimensional array of values.

Tableau allows non-technical professionals at any level to represent data in any format they can understand and transform it into interactive dashboards. It also connects to a wide range of data sources including spreadsheets, databases, and big data platforms.

Features of Tableau

  • Tableau allows you to use natural language to get answers from your data.
  • It connects to data on-premise and on the cloud.
  • It connects to any type of database from the cloud – Salesforce or Google analytics, SQL-based databases(MySQL, PostgreSQL, MariaDB, MongoDB, etc).
  • Tableau has an easy-to-use drag and drops feature.
  • Tableau allows you to easily combine data from different sources.
  • Tableau provides different visualization formats to explore and discover trends in data.
  • Tableau allows creating interactive dashboards and sharing them within or outside an organization.

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Understanding the Key Differences between Apache Superset and Tableau

Now that you have looked at the basics of Apache Superset and Tableau, here is a look at the 4 critical factors you can keep in mind to make an educated guess about Apache Superset vs Tableau and pick the Business Intelligence tool that suits your needs best:

Apache Superset vs Tableau: Platform

Tableau operates on a number of platforms as follows:

  • Desktop
  • Mobile
  • Web
  • Embedded

Tableau can very much operate where you can need it. This provides a major advantage; accessing data from anywhere at any time.

Apache Superset on the other hand primarily works on-premise/on the server. Although, experienced developers can find a way around it to get it running on a desktop. It does not yet support mobile, cloud, embedded as Tableau does. Considering that Apache Superset is newer to the industry than Tableau, more developments will likely roll out to support these platforms in the future. This concludes Apache Superset vs Tableau on the basis of platform features.

Apache Superset vs Tableau: Supported Data Sources

Tableau uses Tableau Prep when connecting to data sources to combine, shape, and clean your data for analysis. Tableau has a built-in data interpreter that does some cleaning when you import your data. Tableau Prep(which is part of the product suite) can be opted for when you need more cleaning for your data.

Tableau supports a wide range of data sources including File type – JSON, PDF, CSV examples include – Microsoft Excel and Access, database connectors from Saas companies – Amazon Redshift, Amazon Aurora, Google BigQuery, IBM BigInsights, Cloudera Hadoop, Dropbox, Microsoft Azure, etc. Tableau also supports ODBC 3.0 connectors and JDBC. ODBC is a SQL-based Application Programming Interface(API) that allows Windows software to access databases via SQL, while JDBC is a SQL-based API that allows Java applications to access databases via SQL.

Apache Superset also supports a large number of databases. The primary ones include:

  • Microsoft SQL Server, Amazon Redshift, Big Query, MySQL, Snowflake, Apache Druid, Firebird, MariaDB, SQLite, Oracle, Postgres, Elasticsearch, Vertica, and some others.

Apache Superset supports any database supported by SQLAlchemy. 

The Apache Superset vs Tableau comparison favors Tableau on the basis of supported data sources. This is because Apache Superset has limited data sources to connect to.

Apache Superset vs Tableau: Authentication and Authorization

Apache Superset security is based on Flask App Builder(FAB) – an application development framework built on top of Flask. This framework supports custom security and authentication in case its authentication methods don’t suit a user’s needs. The major authentication types include: 

  • Databases
  • OpenID
  • LDAP
  • OAuth

Tableau on the other hand requires authentication on different levels. Tableau allows you to set security at the project level or individual dashboard level. This means even if you have access to the server, you might not be able to access some features if you are not authenticated. This does not exist on Apache Superset’s security layer. The authentication types Tableau supports includes:

  • SAML
  • OpenID
  • Active Directory
  • OAuth

Apache Superset vs Tableau: Pricing

Tableau’s pricing is modeled to fit different users. Their pricing plans show that they have their customers in mind. They have pricing for Individuals, Teams/Organizations – this depends on the deployment option(On-premise or cloud) chosen by the organization, and Embedded Analytics. Tableau also allows you to add more licenses to your plans at extra costs.

The pricing plans are quite flexible for users as seen below. For individuals you get the following pricing plan:

Tableau Creator Pricing
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For teams:

Pricing Plan for Teams on Tableau
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Pricing Plans for Teams deploying the solution with Tableau Online
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The pricing for Embedding analytics in an application requires contacting the Tableau sales team. 

Apache Superset breaks the ice here, It is completely free! This concludes the discussion of Apache Superset vs Tableau.

Challenges of Apache Superset

  • Visualization Formats: Apache Superset provides limited visualization formats up to 30.
  • Data Source Connections: Apache Superset connects to only a limited number of data sources.
  • Scope for Growth: The software is still in its development stage and operates only on the server.

Challenges of Tableau

  • Cost: This is one of the major downsides of Tableau. A small organization might not be able to acquire an appropriate package because of the cost. Tableau’s additional licenses also require additional fees to get, so if any organization using Tableau is not well funded, operating at maximum capacity might be a problem.
  • The complexity of software: Tableau is a Data Visualization software with numerous capabilities. It might require an expert to oversee some activities and this might even call for training and certification. Although Tableau is very beginner-friendly, like any other data analysis software, it requires some level of expertise to perform some activities.
  • Backup Irregularity: Tableau does not regularly backup its software.


Tableau and Apache Superset are useful Data Visualization tools with BI capabilities. An organization’s choice would depend on the activities they carry out. This article has analyzed the Apache Superset vs Tableau discussion and examined their capacities. Tableau is a great choice if security and a variety of visualizations are important. It is also a go-to tool if a company will use Embedded Analytics and dashboard sharing to individuals for personal exploration.

Apache Superset is still in its development stage. The contributions from the open-source community are likely to influence its growth in Data Visualization. Both Softwares would get the job done, but a determining factor for choice should be the workload and extensibility.

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