Forest Admin VS superset

Forest Admin is an admin panel solution that saves your back-end engineers time and gives your operational teams more autonomy. Our highly customizable admin panel connects to your databases and APIs to ease your operations so that you can focus more on your business and less on backend operations.

Disclaimer: I'm the founder of Forest Admin.

I couldn't agree more with this statement. The issue isn't that internal tool builders lack a feature to do it, I think the problem is deeper and comes from the way they are designed.

Most of them allow you to build the frontend (web or mobile here) without providing any backend code. They provide you with an integration library, whether it's connecting to a third-party SaaS or to your backend code. But that's where it ends.

With [Forest Admin](https://www.forestadmin.com), we have a completely different architecture. All the backend code is automatically generated with the UI, allowing you to be up and running in a few minutes.

This has allowed us to provide a rich development workflow environment both on the backend (the code is yours and runs on your own machine, so you can use your Git without changing your habits) and on the frontend. This gives you the ability to fork a branch from your production environment to a dev environment, make your changes, merge them on a staging before pushing to prod, etc.

This command line is heavily inspired by Git but allows you to have a dev workflow that works for collaborating with large dev teams on your admin panel. (+100 at our largest customer).

https://www.forestadmin.com https://www.gravitee.io/

I didn't have a spare node app sitting around, so I found Forest Admin. This is actually a cool product which provides the simplicity of dashboard tools like ActiveAdmin or Retool, but preserves the privacy of the data by having you self-host the backend. The backend exposes an API that is used by the frontend client, i.e. your browser, so data doesn't need to move through Forest Admin's servers. Here's a nice graphic to visualize how this works:

Disclaimer: I'm the founder of (Forest Admin)[https://www.forestadmin.com].

Wow, I'm impressed by the number of solutions out there. Back at the beginning of Forest Admin, we were alone on the market, which is generally not a good sign. But our perseverance paid off, and it was definitely worth it in the end!

Alright, so why Forest Admin? :)

Because we only focus on the admin panel use case. Not the entire internal tools world. In this way, we are able to provide a fully-featured SaaS Admin panel out of the box. No need to build it, nor with code, nor with low/no code tools.

Even if your app, internal processes and so your admin panel is specific, we have designed our solution accordingly with 2 things that are part of our DNA from the beginning:

1/ We generate all the backend code required to an admin panel. All CRUD routes, filtering & search, dashboarding, permissions, etc. Everything is automatically generated in a few seconds based on datasource introspection. In the end, the generated code is just a standard REST API, so you can extend/override it without any limitations.

2/ We pre-built the admin UI with every admin standard features available out of the box, with a big focus on providing a great UI/UX possible for operational people. We obviously also provide all the low/no code features to customize pretty much anything. We also provide a feature called "Workspace" (which is generally the core of what our competitors do) that allow users build custom views using drag'n'drop of UI components from scratch.

For home-lab/internal UIs, you can go a long way with the auto-generated model-admin pages from Django. If you just need CRUD and actions triggered on a list of models, you can typically avoid any UI work and just define a few Admin classes, and if you need to make custom forms it's quite easy using Django's templating machinery to override individual pages.

https://docs.djangoproject.com/en/4.0/ref/contrib/admin/

A similar modular admin system that's more generic is https://www.forestadmin.com/, I think this one has a layout editor too. But that one requires a REST API and so it may require more plumbing, depending on what you've already built. Or it could fit nicely on top of what you already have, if you already have APIs for everything.

In this blog, we'll see how to build a CRUD app with Forest Admin. We'll assume you're building a CRUD app for a PostgreSQL database.

At Forest Admin, we build admin panels for which we need to compute and cache large JSON documents. These documents are stored in redis and retrieved from this storage in order to be as fast as possible.

At Forest Admin, we recently faced this issue to move data from a Postgresql database to ElasticSearch.

Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.

https://www.youtube.com/watch?v=RY0SSvSUkMA

https://github.com/apache/superset/discussions/20094

I recently ran a little shootout between Superset, Metabase, and Lightdash. All have nontrivial weaknesses but I ended up picking Lightdash.

Superset the best of them at _data visualization_ but I honestly found it almost useless for self-serve _BI_ by business users. This issue on how to do joins in Superset (with stalebot making a mess XD) is everything difficult about Superset for BI in a nutshell. https://github.com/apache/superset/issues/8645

Metabase is pretty great and it's definitely the right choice for a startup looking to get low cost BI set up. It still has a very table centric view, but feels built for _BI_ rather than visualization alone.

Lightdash has significant warts (YAML, pivoting being done in the frontend, no symmetric aggregates) but the Looker inspiration is obvious and it makes it easy to present _groups of tables_ to business users ready to rock. I liked Looker before Google acquired it. My business users are comfortable with star and snowflake schemas (not that they know those words) and it was easy to drop Lightdash on top of our existing data warehouse.

Or like not being able to delete a user without running some SQL:

https://github.com/apache/superset/issues/13345

Almostl instantly run into this issue setting up a test instance of Superset. And the issue has been around for years.

Are you interested in trying out Superset, but you're intimidated by the local setup process? Worry not! Superset needs some initial setup to install locally, but I've got a streamlined way to get started - using the makefile! This file contains a set of scripts to simplify the setup process.

Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.

if they don't want to pay for powerbi, can try something like https://superset.apache.org/

In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can build a real-time data analytics solution using the open-source tools Redpanda a distributed streaming platform, Apache Superset, a data visualization, and a business intelligence platform, combined with RisingWave a streaming database.