sqlite-utils-jq VS cloudquery

There are a few things you can do here.

SQLite is great at JSON - so I often dump JSON structures in a TEXT column and query them using https://www.sqlite.org/json1.html

I also have plugins for running jq() functions directly in SQL queries - https://datasette.io/plugins/datasette-jq and https://github.com/simonw/sqlite-utils-jq

I've been trying to drive the cost of turning semi-structured data into structured SQL queries down as much as possible with https://sqlite-utils.datasette.io - see this tutorial for more: https://datasette.io/tutorials/clean-data

This is also an area that I'm starting to explore with LLMs. I love the idea that you could take a bunch of messy data, tell Datasette Cloud "I want this imported into a table with this schema"... and it does that.

I have a prototype of this working now, I hope to turn it into an open source plugin (and Datasette Cloud feature) pretty soon. It's using this trick: https://til.simonwillison.net/gpt3/openai-python-functions-d...

Since SQLite supports custom SQL functions, you can add JQ support to it pretty easily.

I just threw together a plugin for my sqlite-utils CLI tool that adds a jq() function here:

https://github.com/simonw/sqlite-utils-jq

Use it like this:

    sqlite-utils memory "select jq(:doc, :expr) as result" \

Check out CloudQuery - https://github.com/cloudquery/cloudquery for an easy cloud asset inventory.

There both do something like what you're looking for.... https://github.com/cloudquery/cloudquery https://github.com/openraven/magpie

Unified API is a holly grail but as many said quite difficult to abstract every use case in a scalable way that won't break. At CloudQuery (https://github.com/cloudquery/cloudquery) we focus solely on the ELT use-case(Founder/Maintainer here).

Congrats!! How does it compare to the ELT space and the modern data stack where you have ingestion/storage/visualization layers decoupled?

Asking as the founder of CloudQuery (https://github.com/cloudquery/cloudquery), Saw Datasette quite a few times around data exploration but curious to hear about the most popular use-cases of Datasette!

Congrats!! We also focus on performance at CloudQuery (https://github.com/cloudquery/cloudquery) by using Golang, gRPC and still trying to be abstract enough to support different databases :)

In any case good luck!

CloudQuery for ETL

Another ELT framework that's an alternative to Airbyte

Another alternate ELT

Check out CloudQuery, we have PostgreSQL source connectors and S3 destination that supports parquet (Disclaimer: Maintainer and founder here)

Hello! Im Yevgeny, Founder & maintainer at CloudQuery . We've built CloudQuery as an open source high performance ELT framework so you should get pretty good results syncing all your cloud assets from high number of accounts (we have users syncing more than 10K Azure subscription and thousands of AWS accounts concurrently).