adroa VS superset

Compare adroa vs superset and see what are their differences.

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adroa superset
1 137
0 58,737
- 3.4%
0.0 9.9
over 2 years ago 4 days ago
Python TypeScript
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of adroa. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-08.


Posts with mentions or reviews of superset. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-26.
  • Apache Superset
    14 projects | | 26 Feb 2024
    Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.

  • A modern data stack for startups
    2 projects | | 30 Dec 2023
    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.

    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.

  • FLaNK Stack Weekly for 20 Nov 2023
    37 projects | | 20 Nov 2023
  • Hiding tokens retrieved via API from the html source?
    1 project | /r/dotnet | 4 Nov 2023
  • Yandex open sourced it's BI tool DataLens
    4 projects | | 26 Sep 2023
    Or like not being able to delete a user without running some SQL:

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

  • Apache Superset Is a Data Visualization and Data Exploration Platform
    1 project | | 11 Sep 2023
  • Apache Superset: Installing locally is easy using the makefile
    3 projects | | 20 Aug 2023
    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.
  • More public SQL-queryable databases?
    3 projects | /r/datasets | 10 Jul 2023
    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.
  • How useful is SQL for managers?
    1 project | /r/learnprogramming | 24 Jun 2023
    if they don't want to pay for powerbi, can try something like
  • Real-time data analytics with Apache Superset, Redpanda, and RisingWave
    3 projects | | 20 May 2023
    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.

What are some alternatives?

When comparing adroa and superset you can also consider the following projects:

cookiecutter-flask - A flask template with Bootstrap, asset bundling+minification with webpack, starter templates, and registration/authentication. For use with cookiecutter.

streamlit - Streamlit — A faster way to build and share data apps.

financeager - Organize your finances easily - from the command line!

jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!

ws-emit - Easily emit websocket events from any sources (python, php, bash, whatever) using redis or HTTP interface

Apache Hive - Apache Hive

vertopal-cli - A small, yet powerful file conversion utility

lightdash - Self-serve BI to 10x your data team ⚡️

Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:

django-project-template - The Django project template I use, for installation with django-admin.

react-admin - A frontend Framework for building data-driven applications running on top of REST/GraphQL APIs, using TypeScript, React and Material Design

nifi - Apache NiFi