dbt-unit-testing VS dbt-core

If you use dbt for transformations Dbt Unit Testing (https://github.com/EqualExperts/dbt-unit-testing) is getting some attention (https://www.thoughtworks.com/radar/languages-and-frameworks?blipid=202304042)

dbt-unit-testing

We use this and take an example-based tests approach for any non-trivial tables: https://github.com/EqualExperts/dbt-unit-testing

> How do you test some SQL logic in isolation?

I do this using sql

1. Extracting an 'ephemeral model' to different model file

2. Mock out this model in upstream model in unit tests https://github.com/EqualExperts/dbt-unit-testing

3. Write unit tests for this model.

This is not different than regular software development in a language like java.

I would argue its even better better because unit tests are always in tabular format and pretty easy to understand. Java unit tests on other hand are never read by devs in practice.

I haven't done it yet but there are some popular blogs as well as a DBT package someone created.

> I really don’t understand the communities obsession with unwieldy tools like DBT.

It lets me write test first sql transforms. I never thought TDD sql would be possible. My sql is so much more readable with common logic extracted into ephmeral models. I practice same method to write clear code to write sql, eg: too many mocks = refactor into separate model ( class) .

I think DBT made this possible with refs that can be swapped out with mocks. This is the awesome library I am using https://github.com/EqualExperts/dbt-unit-testing

it's fun for things you're ok with throwing away.

For example, I wanted a dbt[0] like tool, but written in rust, specifically focused on duckdb. Claude Code knocked it out[1] it without much guidance.

Also added support for all duckdb output options (e.g. write to a partitioned parquet instead of a table).

0 - SQL transformation tool (https://github.com/dbt-labs/dbt-core)

1 - https://github.com/definite-app/crabwalk

Just noticed 404s on dbt core - was this announced recently?

https://github.com/dbt-labs/dbt-core

dbt integration was one of our major goals early on but we found that the interaction wasn't as straightforward as had hoped.

There is an open PR in the dbt repo: https://github.com/dbt-labs/dbt-core/pull/5982#issuecomment-...

I have some ideas about future directions in this space where I believe PRQL could really shine. I will only be able to write those down in a couple of hours. I think this could be a really exciting direction for the project to grow into if anyone would like to collaborate and contribute!

I really dislike SQL, but recognize its importance for many organizations. I also understand that SQL is definitely testable, particularly if managed by environments such as DBT (https://github.com/dbt-labs/dbt-core). Those who arrived here with preference to python will note that dbt is largely implemented in python, adds Jinja macros and iterative forms to SQL, and adds code testing capabilities.

3). Data Build Tool Repository.

dbt Cloud rightfully gets a lot of credit for creating dbt Core and for being the first managed dbt Core platform, but there are several entrants in the market; from those who just run dbt jobs like Fivetran to platforms that offer more like EL + T like Mozart Data and Datacoves which also has hosted VS Code editor for dbt development and Airflow.

Ahh I misunderstood, yes column level lineage is useful. DBT prefers leveraging macros which sort of breaks this pattern. I think the DBT way would be to better separate fields into upstream models and use table tracking https://github.com/dbt-labs/dbt-core/discussions/4458