Tools we love – Redash

  • Product Reviews

Redash is an awesome open-source business intelligence tool used for creating interactive dashboards and to create meaningful visualizations. Redash is designed to enable anyone – regardless of their technical knowledge – to harness the power of data big and small. We have leveraged the power of Redash to build, a powerful open-source forms workflow analytics solution framework.

redash logo


What is unique about Redash?

Some of the unique features which make Redash stand out are:

  • It supports extensive data source API with native support for about 30+ databases and platforms.
  • Quickly compose SQL and NoSQL queries with a schema browser and auto-complete.
  • Create beautiful visualizations with drag and drop, and combine them into a single dashboard, which can be refreshed automatically at regular intervals.
  • We can collaborate easily by sharing visualizations. Also, it can be embedded in websites and shared with colleagues enabling peer review of reports.
  • We can define conditions that will be alerted instantly when data pass a threshold.
  • Support for a variety of authentication options like SSO, Google OAuth, SAML.
  • Everything that can be done in the UI is also available through REST API.
  • Using data you can make informed decisions based on visualization and without the need to master any complex software.

redash visualization

Why we love Redash?

We obviously love Redash because of its powerful features. Yet that is not the only reason we chose Redash as our analytics platform for If you look at the market of Business Intelligence tools, there are a lot of choices, both proprietary and open-source. Even in open-source space, there are a lot of products like Apache Superset, Dash (based on Plotly), RawGraphs, etc which are feature-rich and powerful.

Another reason we use Redash is that it supports the authentication method of OpenID Connect(OIDC) needed for with SAML authentication. Also, it is very light-weight to use for our entire application compared to other providers. Lastly, Redash is open-source and has a stable community to help out any time.

How to use Redash?

The process of how to use Redash is well documented in official docs. Some of the basic steps for working with Redash are:

1. Add Data sources – You can connect with about 30+ supported data sources mentioned in docs from the browser itself.

redash data sources

2. Write Queries – Once data is connected we can write queries. It’s always ideal to create individual queries for the necessary visualizations. Writing queries is a data preparation step to process data for visualization.

redash queries

3. Create Visualizations – There are a variety of visualizations supported in Redash. Ten different categories of visualization can be created with just drag and select features to visualize from the queried data. Redash supports visualization types like BoxPlot, Counter, BarCharts, Sunburst, Sankey, Word Cloud, line chart, Area charts, etc. To learn how to create visualizations checkout Redash visualization docs.

redash sankey sunburst diagrams

4. Create dashboards – We can create interactive dashboards that can be embedded anywhere and shared with colleagues easily. The queries can be refreshed periodically as more data comes in.

redash dashboards

Redash has 17,400+ stars in Github. It’s used by millions of users at thousands of organizations around the world, which is the best measure to show the stability of the product.

To sum up we recommend you to use Redash when:

  • To create beautiful and interactive dashboards
  • Use as an alternative to libraries like Matplotlib, Plotly,etc. to create visualizations at a faster pace.
  • To make your decisions data-driven
  • Use a powerful query engine similar to SQL
  • To make use of 30+ supported data platforms in Redash


Redash Knowledge Base

Redash github Readme getting started

About the author:

Kurian Benoy is a SE-Data scientist at AOT Technologies. He is a Kaggle expert, with an interest in working on data science problems. He was a Google CodeIn mentor for Tensorflow in 2019, and has worked for open-source organizations like Keras, DVC, Swathanthra Malayalam Computing.
In his free time free, he likes to do bird watching and takes interest in learning more about world history.