Continuing discussion from GitHub. What are some similarities and differences between the Redash and Apache Superset projects? Are there some similarities that might be worth a cross-project collaboration?

Here are some ‘dimensions’ by which to compare Superset and Redash, and open-source projects in general.

Supported databases

A data source compatibility table might be a deciding factor. Caveat emptor, maintaining integrations with multiple databases is likely difficult work and may not have consistent functionality across integrations in a single project, let alone across the two projects.

Data source Redash Superset
Amazon Athena
Amazon Aurora
Amazon DynamoDB
Amazon Redshift
Axibase Time Series Database
Cassandra
ClickHouse
druid
Elasticsearch
Google BigQuery
Graphite
Greenplum
Hive
Impala
InfluxDB
Microsoft SQL Server
MongoDB
MSSQL
MySQL
Oracle
PostgreSQL
Presto
ScyllaDB
SparkSQL
sqlite
TreasureData
Vertica
Google Analytics
Google Spreadsheets
JIRA

Documentation

It is worthwhile to compare documentation of the two projects.

  • Is there a user guide?
  • Is there an administrator guide?
  • How easy is it to find the documentation?
  • How easy is it to contribute to the documentation?

Installation option(s)

  • How easy is it to set up an instance on your local computer to ‘try-it-out’?
  • How easy is it to install a production-ready instance?
  • How easy is it to set up a development environment?

Development activity

  • How many active contributors does each project have?

  • How quickly do issues and PRs get resolved (on average)?

  • Is there a CONTRIBUTING.md?

Project management

  • Is there a ROADMAP?
  • Does the project use Continuous Integration?
  • How extensive is test coverage?

Community

  • Is there a CODE OF CONDUCT?
  • Is there a community discussion forum (e.g. Discourse)?
  • Is there a real-time channel for chat?
1 Like

Thanks! I changed this post type into a Wiki.

(Btw, it’s Redash and not Re:dash anymore)

I tried Superset first. In a graph with YEAR on the X axis and quantities on the y axis, years (x) were ordered by magnitude of y value descending, not by any (alpha, numeric) sort order on x, so the years would be out of order. ISSUES showed the problem was longstanding and not resolved. Finally, Superset did not appear to support multiple users at the same time.
Then I tried Kibana graphing and converted my data to ElasticSearch for a trial. In addition to the indexing cost, there were some annoying issues with Kibana’s treatment of dates and date display (UT vs. local) and an opaque graphing interface. So I tried grafana which was impenetrable due to lack of setup documentation.
I have now settled on Redash, because it gives the graphic control that Superset lacked, along with connectors to a large number of data sources (including ElasticSearch). Additionally, Redash is the easiest to work with (SQL and a few minimal guidelines).
For me there’s no question that Redash is the best open-source choice of those I tried.

(@imbroglioj on GitHub)

Superset supports druid.io. I haven’t seen support of that datasource on Redash (see). Am I wrong?

Also in a comparison it would matter most the support for parameters, filters, embedding, dashboard widgets available, dashboards flexibility. That’s a few areas where superset is really lacking imho.

Superset has a bold vision and incorporates lots of features. But they don’t care much about quality and that is why documentation is misleading and setup instruction confusing. But also usability is poor as you will encounter bugs and unintuitive interfaces. I talked to bunch a bunch of people of other companies and they tell the same. Redash instead cares more about quality but has less visualisation. But at least you can rely on them.

I wrote more details in an article https://medium.com/@c.lingg/apache-superset-vs-redash-5951cc2da9d