dbt-core VS grouparoo

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!

> Could you share more specific details? Happy to look over / revise where needed.

Sure thing! I'd say first off, the solutions may look different for a small company/startup vs. a large enterprise. It can help if you explain the scale at which you are solving for.

On the enterprise side of things, they tend to buy solutions rather than build them in-house. Things like Informatica, Talend, etc. are common for large enterprises whose primary products are not data or software related. They just don't have the will, expertise, or the capital to invest in building and maintaining these solutions in-house so they just buy them off the shelf. On the surface, these are very expensive products, but even in the face of that it can still make sense for large enterprises in terms of the bottom line to buy rather than build.

For startups and smaller companies, have you looked at something like `dbt` (https://github.com/dbt-labs/dbt-core) ? I understand the desire to write some code, but often times there are already existing solutions for the problems you might be encountering.

ORM's should typically only exist on the consumer-side of the equation, if at all. A lot of business intelligence / business analysts are just going to use tools like Tableau and hook up to the data warehouse via a connector to visualize their data. You might have some consumers that are more sophisticated and may want to write some custom post-processing or aggregation code, and they could certainly use ORM's if they choose, but it isn't something you should enforce on them because it's a poor place to validate data since as mentioned there are different ways/tools to access the data and not all of them are going to go through your python SDK.

Indeed in a large enough company, you are going to have producers and consumers that are going to use different tools and programming languages, so it's a little bit presumptuous to write an SDK in python there.

Another thing to talk about, and this probably mostly applies to larger companies - have you looked at an architecture like a distributed data mesh (https://martinfowler.com/articles/data-mesh-principles.html)? This might be something to bring to the CTO more than try to push for yourself, but it can completely change the landscape of what you are doing.

> More broadly is the issue of the gap of what you think the role is, and what the role actually is when you join. There are definitely cases where this is accidental. The best way I can think of to close the gap is to maybe do a short-term contract, but may be challenging to do under time constraints etc.

Yeah this definitely sucks and it's not an enviable position to be in. I guess you have a choice to look for another job or try to stick it out with the company that did this to you. It's possible there is a geniune existential crisis for the company and a good reason why they did the bait-and-switch. Maybe it pays to stay, especially if you have equity in the company. On the other hand, it could also be the case that it is the result of questionable practices at the company. It's hard to make that call.

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

Here’s the PR, which includes a what/how/why: https://github.com/dbt-labs/dbt-core/issues/7158

I've attached a link to their documentation. DBT is becoming increasingly popular within the Data Engineering community with over 5k stars on github.

Reverse ETL is on AirByte's roadmap under the "Future / Not prioritized" section. I wanted to use Grouparoo as a short term solution, but the repo was archived and I think they stopped taking new cloud customers (unknown if this is wrong/outdated).

There are other tools that we will have to adopt in the future but haven’t yet due to lack of necessity. Specifically, one category that is popular in modern data stacks is Reverse ETL (Hightouch, Census, or Grouparoo). We currently don’t have a usecase for piping data back into 3rd party tools but it will definitely come up in the future.

Reverse ETL: Grouparoo, Castled

Grouparoo, the open source Reverse ETL tool we are building, does all of these things. https://www.grouparoo.com

Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset

Grouparoo | Remote (US) | Remote-OK | https://www.grouparoo.com

Grouparoo is a venture-backed software company building open source data tools that make data reliable, accessible, and actionable. We’re empowering teams to make great customer experiences, driven by data. While engineering teams have gotten good at storing and generating data about their customers, it’s rare that this data is used to its full potential in external applications. Grouparoo makes these integrations easy by providing a framework for defining your customer data and reliably syncing it to external tools.

To learn more about who we are, our engineering culture, and whether this is the right place for you, read our Key Values profile: https://www.keyvalues.com/grouparoo

Here are our open roles:

- Senior Backend / Lead Engineer: https://jobs.lever.co/grouparoo/6ba485d1-a5a4-41f0-9fa5-920a...

- Developer Advocate: https://jobs.lever.co/grouparoo/5e1531b4-7ec8-4c10-8e52-fc23...

Tech Stack: TypeScript / Javascript / Node.js, ActionHero, React + Next.js, Postgres & Redis, and whole lot of third-party APIs!

Congrats on the launch! Hightouch looks great and this need is real. Things seem to be going well, so I don't think I'm taking too much away by mentioning that we have been been working on Grouparoo, an open source alternative that solves similar pain points.

A few differences: git developer workflow focused (branches, CI, PRs, etc), ability to self host, segmentation in destinations (tagging people in mailchimp based on rules, for example)

https://www.grouparoo.com

We are building Grouparoo. Obviously, it's a biased sample but we are seeing a few trends at play.

Has anyone heard or used of reverse etl or Hightouch or open sourced Grouparoo?