obsidian-dataview VS superset

At the end of the day, I use Dataview, a plugin for Obsidian, which allows me to make queries to my notes similar to SQL to visualize the collected information:

https://github.com/blacksmithgu/obsidian-dataview

This whole ideas to have data, visualisations and knowledge base in one private offline place is very appealing

Since at least 2012 I've also been using a text file format from http://todotxt.org/ and more recently I wrote a program that takes a crontab-like list to pre-generate entries on a daily, by-day-name (every Sunday for example), and I also pull in a list of holidays from gov.uk, so they are also populated.

[^1]: (https://github.com/blacksmithgu/obsidian-dataview)

> Joplin is using md to.

The way it's handled can make the difference in control.

> by separating that in their DB, it's a big NO for me since it's a closed silo.

Joplin is using a popular open database with a healthy community and good tooling. It's as open as markdown. Maybe not for you, when you lack the knowledge, but markdown is similar closed for anyone not understanding filesystems and editors.

> This: https://github.com/blacksmithgu/obsidian-dataview works so wonderful for me

Good for you, but that is very low level in terms of data-handling. Dataview is really just an elaborated search, there is no good level of interaction. Datacore, the next project of the Dataview is supposed to bring this, but it's not even usable yet AFAIK. Coincidental, the Obsidian-devs are also working on that front, but nothing is finished yet.

> https://github.com/denolehov/obsidian-git and b) easy to fix since it's a text file. Gosh!

That's useless when the app itself is not working. And even worse if you are not realizing the errors early.

> Aha. I don't think so. Which authority says that?

My own experience. I've tested enough plugins over the years to know their dark corners.

> And even if It's like that, my markdown files would survive everything

The thing is, technically you are not even having proper markdown, but a fork with some extensions of Obsidian. So some features of your parts might break when switching away from Obsidian. And the reason for all this is also because markdown is lacking definitions for what obsidian-people are doing with it. Coincidentally, this seems also one of the reasons why Joplin is using a database.

> And gosh, this is a good thing!

Not if they all suck.

> Installing multiple task plugins shows that something is "broke" on the user side.

Sure, because the plugins are lacking features, its the users fault... Maybe some users have just very different levels of requirements from you.

Refer: Obsidian Search, How I Use Embedded Queries, Dataview, Excalibrain

Ref: https://github.com/blacksmithgu/obsidian-dataview/issues/544 (Bearbeitet)

For using it, having SQL or JavaScript knowledge is useful, but you can probably figure it out without that knowledge. The Github page has a lot of examples that you can cannabalize for simple things without really getting too deep into it.

Check it here.

I think this could be helpful https://github.com/blacksmithgu/obsidian-dataview/issues/1086

Have you heard of Obsidian? It's a note-taking app build on locally stored markdown files with bidirectional linking and a great ecosystem of third party plugins. One of the most popular plugins is https://github.com/blacksmithgu/obsidian-dataview which lets you treat your notes as databases and query them to form tables. The creator has been working on its successor, Datacore https://github.com/blacksmithgu/datacore for a while - Datacore might come close to what you're looking for, its goals include WYSIWYG views and live editing inside tables.

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.