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Meltano raises $4.2M seed round

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Re: Meltano raises $4.2M seed round

#21
post #14

From an employee/engineering perspective, spinning out products with seed funding sounds like the coolest possible way to approach growth for established companies. The idea you could work somewhere big and then have the opportunity to do a startup with a direct piece of the upside seems amazing. From a product perspective, you get a clean slate and some sales support from your old company who have a stake in seeing…

Clayton Christensen wrote about this extensively in The Innovator's Dilemma. I read it and enjoyed it

Also, Peter Thiel's Zero to One

Re: Meltano raises $4.2M seed round

#22
post #20
post #11

Earlier quoted context omitted.

Meltano is an open source platform for ELT (Extract, Load Transform) pipelines that leverages Singer for data integration and dbt for transformation. It may not be clear from the blog post (since it's not focused on introducing the product), but I hope the homepage would get that across: https://meltano.com/ Please let me (Meltano CEO) know how we could make that more obvious!

Hi ... Get some corridor feedback :) ELT isn't explained, and probably a few other terms as well. It's just not clear what either the value or purpose is. In my opinion, that is.

Yeah, ELT is really pretty simple it gets hyped up too much as being super innovative. DEV time is expensive so optimize for it instead of saving CPU cycles / disk space.

Instead of trying to save space in your destination app by filtering data and only pushing what you need into your Database/Datawarehouse (Snowflake, Redshift, Postgres, MSSQL, etc) throw all of your data from your sources into the Database. They are super fast and storage is cheap. The expensive thing now is DEV time so optimize for that.

Re: Meltano raises $4.2M seed round

#23
post #9

Earlier quoted context omitted.

Meltano is a open source platform for automating ELT pipelines.

Is there any significant difference from the traditional ETL?

The idea is lean towards doing no transformation before loading into your Target Database/Datawarehouse. Do all transformations after the data hits your target database. DEV time is expensive, storage and CPU is cheap now. DBs and DWs are blazing fast now.

You can still only pull the data that you need using Meltano, but you select things on a "Stream" / "Attributes" level. For source DBs this means something like Table and Field level is as granular as you get.

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