Apache Superset vs Tableau: 4 Critical Differences

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.

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:

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.

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.

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
• REMOTE_USER
• 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

Visualization

Apache Superset comes with rich visualizations and dashboards that help users to explore the dataset using the array of Data Visualizations. The interactive dashboards help users view real-time data updates and monitor business activities. Also, it comes with SQL Lab that allows them to investigate the data thoroughly.

Tableau allows companies to organize and present data intuitively. It allows users to drill down into data and create hierarchies for easy access and understanding of data better. Tableau Filters help users to filter out the data easily so that they can analyze data deeply. Users can easily drag and drop their data into beautiful visualizations.

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:

For teams:

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.

Conclusion

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. Compare Apache Superset and Tableau to determine the best data visualization tool for your specific needs. 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.

Extracting complex data from a diverse set of data sources to carry out an insightful analysis can be a challenging task and this is where Hevo saves the day! Hevo offers a faster way to move data from Databases or SaaS applications into your Data Warehouse to be visualized in a BI tool such as Tableau or Apache Superset. Hevo is fully automated and hence does not require you to code. You can try Hevo for free by signing up for a 14-day free trial. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.