superset
appsmith
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superset | appsmith | |
---|---|---|
137 | 233 | |
57,792 | 31,240 | |
2.4% | 2.4% | |
9.9 | 10.0 | |
5 days ago | about 1 hour ago | |
TypeScript | TypeScript | |
Apache License 2.0 | 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.
superset
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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.
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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
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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.
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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.
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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.
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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.
appsmith
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
appsmith β Low code project to build admin panels, internal tools, and dashboards. Integrates with 15+ databases and any API.
- Why I'm skeptical of low-code
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How to build a Google Meet AI assistant app in 10 minutes without coding
Effective communication and efficient meeting management are key to a team's success in the modern workplace. Recognizing this, we will develop an AI-powered meeting assistant app to transform Google Meet recordings into automatically generated meeting notes with key takeaways and action items. The blog post is tailored for every creator from developers to no-coders who are interested in the intersection of AI and productivity tools. It's particularly useful for those with limited AI-development experience and who want to build AI applications by using simple low-code tools like Unbody and Appsmith.
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π₯π₯ Our awesome OSS friends π
Appsmith- Build build custom software on top of your data.
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The Ultimate Guide to Building Internal Tools in 2024
Suggest features and help to guide Appsmithβs future: Appsmith's community keeps us at the forefront of internal tools with feature requests for the latest third-party integrations and robust community support.
- Ask HN: Why did Visual Basic die?
- Exploring Top 9 Retool Alternatives for Enterprise Applications in 2023
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How to Write a Great Readme
> https://github.com/appsmithorg/appsmith
That is more of a GitHub landing page than a readme.
> An effective README file needs to tell your audience what your project does, how to use it, and how they can help out.
The readme starts with a `a` image tag nested within a `p`.
One spot where your readme misses the mark: it can't be read outside of github (or some rendering engine). Markdown is supposed to be human readable. Instead you say "here's how app smith works" and then plop a big image. That doesn't help anybody understand what your project does by reading the readme. Images and diagrams are super helpful, but they should accompany thoughtful prose. This is also important as an accessibility consideration.
The contributors sections are dumb. Github is a better tool to use to view contributors (https://github.com/appsmithorg/appsmith/graphs/contributors). Other projects before github would have an authors and/or contributors file. I don't care about the contributors when I'm trying to understand how your project works, it's just shameless marketing in that position.
You have a "getting started in 100 seconds" image CTA in your features section. Doesn't make any sense to me.
Overall I'd suggest focusing on improving your readme to be more useful and less of a marketing tool (it can still market its value lightly) and instead explain how the software works and how to get up and running with it.
Overall I'd score your readme 4/10.
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Managing AI-powered Java App With API Management
In this tutorial, we explored the OpenAI ChatGPT API to generate responses to prompts. We created a Spring Boot application that calls the API to generate responses to prompts. Next, you can introduce additional features to your integration by updating the existing apisix.yml file. Also, you check out the branch name called with-frontend and run the project to see the UI interface built using Appsmith that works with APISIX.
What are some alternatives?
ToolJet - Low-code platform for building business applications. Connect to databases, cloud storages, GraphQL, API endpoints, Airtable, Google sheets, OpenAI, etc and build apps using drag and drop application builder. Built using JavaScript/TypeScript. π
budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes π
streamlit - Streamlit β A faster way to build and share data apps.
react-admin - A frontend Framework for building data-driven applications running on top of REST/GraphQL APIs, using TypeScript, React and Material Design
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
Apache Hive - Apache Hive
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
lightdash - Open source BI for teams that move fast β‘οΈ
Directus - The Modern Data Stack π° β Directus is an instant REST+GraphQL API and intuitive no-code data collaboration app for any SQL database.
Strapi - π Strapi is the leading open-source headless CMS. Itβs 100% JavaScript/TypeScript, fully customizable and developer-first.
nocodb - π₯ π₯ π₯ Open Source Airtable Alternative