Rath
superset
Our great sponsors
Rath | superset | |
---|---|---|
43 | 137 | |
3,921 | 57,792 | |
3.4% | 2.4% | |
7.1 | 9.9 | |
2 days ago | 5 days ago | |
TypeScript | TypeScript | |
GNU Affero General Public License v3.0 | Apache License 2.0 |
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.
Rath
- FLaNK Stack for 15 May 2023
-
Observable Plot: The JavaScript library for exploratory data visualization
Big fan of D3.js and now there is Observable Plot! I am building several data visualization software for exploratory data analysis:
RATH, auto exploratory data analysis: https://github.com/Kanaries/Rath
GraphicWalker, embeddable data exploration component: https://github.com/Kanaries/graphic-walker
They are using vega-lite for now. But there is a limit of building more fancy and customized visualizations. It seems Plot has a more flexible layer based visualization system that can support larger design space.
Is Plot stable enough now to migrate from vega-lite based system to Plot based? Are there any large milestone or roadmap of Plot in future?
- Show HN: RATH – Open-Source Copilot and Autopilot for Data Analysis
-
How to send emails in Node.js (Detailed Steps)
I am also working on an Awesome Open Source project named: RATH. Check it out on GitHub!
-
Ask HN: What do you use for basic data analysis, visuals, and graphing?
I'm considering https://github.com/Kanaries/Rath, which seems to be an OSS version of Tableau. Has anyone used it for this type of thing?
-
Show HN: Turn Your Pandas Dataframe to a Tableau-Style UI for Visual Analysis
Ah, there’s a really nice profiler implemented in one of their other projects here (AGPLv3): https://github.com/Kanaries/Rath/tree/master/packages/rath-c...
There’s a lot of really nice features in this other tool, the author’s thought of everything: https://github.com/Kanaries/Rath
-
6 Ideas for building ChatGPT Chrome Extensions
Don't forget to check out my GitHub project:https://github.com/Kanaries/Rath We are also having a website for RATH now!
-
Data Painter – A Different Way to Interact with Your Data
It allows you to do on-flight data labeling, cleaning, or even create new features does not exist in the original dataset. Everything can be done with a brush tool(painter), You can even play with your data with your fingers on mobile. RATH is an open-source alternative to Tableau, but with more automation. Feedback and suggestions are appreciated! Read Data Painter Docs for more details, or check out RATH GitHub.
-
MCM/ICM 2023 is Here (Download historical MCM/ICM Problems)
RATH is an Open Source Automated Data Analysis and Visualization tool that can help you uncover insights and patterns in your data quickly and efficiently. Check out RATH Source Code on GitHub and Free RATH Playground.
superset
-
Apache Superset
Had a very good experience with Superset.
Superset allowed us to replace Tableau and not looking back
Took me a while figure out how to embed it into my app using Superset Embedded SDK.
Superset Embedded SDK - "Embedded SDK allows you to embed dashboards from Superset into your own app, using your app's authentication. Embedding is done by inserting an iframe, containing a Superset page, into the host application."
https://github.com/apache/superset/tree/master/superset-embe...
Superset is based on very high quality and well maintained chart library eChart
https://echarts.apache.org/examples/en/#chart-type-linesG
Community Roadmap
https://github.com/apache/superset/projects?query=is%3Aopen
Huge respect to Preset.io and its team for contributing to the project and keep it in a great shape
Superset source code is very easy to read and understand, and as a result it's possible to implement some advanced caching techniques reduce the load on charts.
No BI is perfect.
Watching Superset for years gives me confidence the project will work as supposed down the road, and eventually some of its packages can be reusable for all kind of visualizations and data hacking.
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
Do you have any thoughts on Superset? Did you consider it as a candidate?
For anyone who doesn't know: https://superset.apache.org/
(There's at least one service that offers managed Superset hosting if that's what you're looking for; it's easy to find so I won't link it here.)
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.
- FLaNK Stack Weekly for 20 Nov 2023
-
Yandex open sourced it's BI tool DataLens
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.
-
Apache Superset: Installing locally is easy using the makefile
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?
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.
-
Real-time data analytics with Apache Superset, Redpanda, and RisingWave
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?
streamlit - Streamlit — A faster way to build and share data apps.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
Apache Hive - Apache Hive
lightdash - Open source BI for teams that move fast ⚡️
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
Baserow - Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
appsmith - Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.
dagster - An orchestration platform for the development, production, and observation of data assets.