Superset vs Metabase vs Redash – Comparing Open Source BI Tools

on Analytics • September 12th, 2017 • Write for Hevo

A human brain retains more information through patterns and visuals as compared to reading or studying numbered files. In the business world, visualization is imperative in understanding the significance of data. Let us understand with an example.

An e-commerce company receives thousands of orders per day. For studying the weekly performance, a graphical plot showing the number of orders per day will result in faster interpretation than a spreadsheet comprising the order details.

Hence, visual data representation is a powerful technique.  It helps companies in analyzing trends and gaining valuable insights which further helps in decision making.

Open source data visualization tools like Redash, Metabase, and Apache Superset are gaining popularity as the learning curve isn’t steep for non-technical users. A large number of startups are using Metabase, Redash, and Superset to query, collaborate and visualize.

This blog talks about the Metabase vs. Redash vs. Superset over a few parameters.

1. Data Sources:

The widely used data warehouses- Amazon Redshift and Google BigQuery and databases like MySQL, PostgreSQL are supported by all the three visualization tools. Snowflake is supported by Metabase and Redash. Cassandra is supported only by Redash. Below is a list of data backends supported by Metabase, Redash, and Superset.

Data SourcesMetabaseRedashSuperset
Amazon Redshift
Google BigQuery
Google Analytics 
Microsoft SQL Server

2. Extension Platform:

It is simple to extend open source BI tools if required. Metabase apparatus is developed on Clojure whereas Redash and Superset are based on Python. This helps you to decide which tool is favourable if your company uses the same platform – Python or Clojure.

3. Authentication Support:

Superset provides richer options in terms of authentication. While Metabase and Redash have support for Google OAuth and SSO only, with Superset you can also integrate your in-house authentication backends or LDAP.

ToolGoogle OAuthLDAPOpenIDDatabase

4. Access Control and Permissions:

While using Metabase, Redash, and Superset at an organizational level it is important to understand the access controls. One can restrict access to databases, queries, and dashboards as per the requirements.

Metabase and Redash follow a group-based approach to provide access control and set permissions. One can be a member of multiple groups. The level of access to databases and SQL is determined by group membership.  

For instance, when you are a part of a group, you have access to all the databases in the group. Your permissions are tabulated as per the level of access, groups, databases, etc. in the permissions’ section of the admin panel.

Superset has different levels of access control: Admin, Alpha, Gamma, and Public.

  • Can grant and revoke rights from fellow users
  • Can make changes in slices and dashboards of other users
  • Access to SQL Lab – can grant access to  Alpha and Gamma users
  • Access to all data sources in Superset – can add and alter them
  • Can’t grant or revoke access
  • Limited access to the owned objects
  • Can only consume data they have given access to
  • Can’t add or alter data sources
  • Can create slices and dashboards
  • Logged out users have can view dashboards
  • Useful for enabling  access to anonymous users

Want to learn more about BI and Data Visualisation tools? Here’s a detailed Hevo 
post on Periscope vs Chartio vs Looker .

Data Pipeline, Data Warehouse, and Data Visualisation are three components of a Data Integration Stack. In this post, we learned about open-source visualization tools.

We, at Hevo, are building the most robust and comprehensive ETL solution in the industry. We integrate with your in-house databases, cloud apps, flat files, clickstream.  Drop us your queries at

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