Redash VS plotly

redash

In addition to metabase there are redash[0] and apache superset[1]. They are more or less similar to metabase with some different quirks. You can also visualize quite a bit of data in grafana[2] as well.

[0] https://redash.io/

[1] https://superset.apache.org/

[2] https://github.com/grafana/grafana

Source: https://github.com/getredash/redash/graphs/contributors

How does it compare to Redash (now Databricks SQL): https://github.com/getredash/redash?

There seems enough competitors when this looks like a tool from 20 years ago with limited functionality.

If you somehow do not use the obvious GUI tools like TablePlus, Postico or SequelAce but prefer web based, there are some that actually look modern.

https://www.getmotoradmin.com/

https://www.nocodb.com/

https://redash.io/

For readonly usage, Metabase is good.

Something like https://redash.io with https://n8n.io connected to InfluxDB?

Without some dev/programming experience, it will be tough. But redash is a great Open Source tool to collect to data sources and show dashboards. Here is the GitHub

we use a self hosted redash instance to visualize the data with dashboards and whatnot.

- plotly (https://plotly.com/python/);

Sure! One of the big ones that really powers the whole web application is Python Dash. This framework lets you build an entire web application in pure python, similar to something like Flask or Django, but its geared more towards data science applications. You get to use all of the Plotly charts in a streamlined way. 🙌 Dash actually uses React under the hood to render the web page, and there's a lot of useful 3rd party libraries with ready-to-use web components.

They have a lot of detailed examples on https://plotly.com/python/

(I don't know how to run it if it's installed as a package, but this works great and is much easier to customize. Plotly has pretty graph/chart options by the way https://plotly.com/python/ )

Focus on Documentation We get more traffic to our documentation than our main website. A well-documented project is always loved by the community. Open-source projects like Docusaurus make it super easy to build documentation portals that look great just out of the box. Adding links to the repository from the documentation can drive more visitors to your repository. What to include in documentation How to install/deploy the project If the project has a compiled software as the final product, make sure to add installation instructions. If the project is the codebase for a library such as an npm package or a Ruby gem, include details on how to import and use the library. If the project needs to be or can be deployed on platforms like Kubernetes, Docker, Heroku, and others, include separate guides for each of the options. Contributing guide Apart from the contributing guide doc in the codebase, add one to the documentation, too. It should include guides for setting up a local environment on different platforms like Docker, Mac OS, Ubuntu, Windows, and so on. Tutorials and code examples If this is applicable, it can be really helpful. How to guides on using using the project will show other devs how they can actually get started. It can be code examples if the project is a library. Architecture reference It will be helpful for the contributors if the documentation has details on different components of the project. For example, if the project has server and client components, include a diagram on how everything works together. Here are some projects with great documentation: https://docs.nestjs.com/ https://docs.n8n.io/ https://guides.rubyonrails.org/ https://plotly.com/python/ https://docs.mapbox.com/ https://www.github-stars.com or Github24.

Data visualization: matplotlib, seaborn, bokeh, dash / plotly, etc.

Plotly Graph Guides