airbyte VS meltano

I'l also give a shout-out to Airbyte (https://airbyte.com/), with which I've had some limited success with integrating Salesforce to a local database. The particular pull for Airbyte is that we can self-host the open source version, rather than pay Fivetran a significant sum to do this for us.

It's an immature tool, so I don't yet know that I can claim we've spent _less_ than Fivetran on the additional engineering and ops time, but it feels like it has potential to do so once stabilized.

Link to GitHub -->

When it says "available in open source", is that under the main airbyte repo's licensing [1], hence primarily licensed under the Elastic License v2 and therefore not typically considered open source by many?

Airbyte has previous of advertising their offering as open source while not really being as per the OSD[2]. This has been raised with them previously but without response [3][4]. They've also been extending their use of ELv2, recently moving many of their existing MIT licensed connectors to be ELv2 [5].

[1] https://github.com/airbytehq/airbyte/blob/master/LICENSE

As possible solution, I can suggest Airbyte(https://airbyte.com/). it's more performant than generic python script.

Airbyte, an open-source data integration engine that offers hundreds of connectors with data warehouses and databases, has gained popularity for its seamless integration and data syncing capabilities. Xata's integration with Airbyte offers a streamlined data ingestion process from any Airbyte input source directly into your Xata database.

You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte

I would use something like meltano or airbyte, but if you really want to use Lambda for extraction I'd say there is no point spinning up a Redshift cluster just for that, Athena would be the way to go and you can use dbt pretty nicely with it and it would keep costs down.

Airbyte and Singer/Meltano if you want to learn more about ingestion pipelines. Airbyte and Meltano teams are very welcoming. SQLfluff a shiny SQL linter. Beautiful project with awesome maintainers.

I know really sure if this is what are you looking for, but take a look at Meltano

I'm not aware of any. I did just open this issue[0] in the Meltano project to open discussion with the team/community. It could be an interesting iteration on the Singer Spec[1] if we find that users are interested in it and it helps solve some bottleneck challenges.

[0] https://gitlab.com/meltano/meltano/-/issues/2616

Good point! As expected, there's an issue about adding it already: https://gitlab.com/meltano/meltano/-/issues/1175

At GitLab, we're not ready to give up on the Singer spec, community, and ecosystem yet, which is why I've been working on Meltano for the past year: https://meltano.com/

We think that the biggest things holding back Singer are the lack of documentation and tooling around taking existing taps and targets to production, and around building, debugging, maintaining, and testing new or existing high-quality taps and targets.

Meltano itself addresses the first problem, and provides a robust and reliable platform for building, running & orchestrating Singer- and dbt-based ELT pipelines.

At the same time, we have been working with some members of the community on a new framework for building taps and targets: https://gitlab.com/meltano/meltano/-/issues/2401, which we have decided to call the Singer SDK: https://gitlab.com/meltano/singer-sdk