dagster VS meltano

My recommendation is to continue on with the tutorial, then look at one of the larger example projects especially the ones named “project_”, and you should understand most of it. Of what you don't understand and you're curious about, look into the relevant concept page for the functions in the docs.

I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured

I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home

In Helm terms: there are 2 charts, namely the system: dagster/dagster (values.yaml), and the user code: dagster/dagster-user-deployments (values.yaml). Note that you have to set dagster-user-deployments.enabled: true in the dagster/dagster values-yaml to enable this.

Dagster seemed really cool when I looked into it as an alternative to airflow. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. However it seems it does not support RBAC which is a pretty big issue if you want a self-service type of architecture, see https://github.com/dagster-io/dagster/issues/2219. It does seem like it's available in their hosted version, but I wanted to run it myself on k8s.

Dagster? https://dagster.io

One that I haven't seen on here yet: dagster

- https://github.com/meltano/meltano

We'd love to hear what you think of Meltano (Cloud). If you join the Beta, you get 100 free credits (200 hourly or 100 daily runs) and a 20% discount on the pricing at GA (June 27). The first 100 to sign up get 1,000 credits -- that's 83 days of hourly runs or 3 years of dailies!

The team and I will be checking in here throughout the day, so don't hesitate to ask questions! If we don't get to you, feel free to join 3,500+ Meltano fans on https://meltano.com/slack and we'll chat there!

Meltano[0] might be of interest to you. Easy way to move data that should be very familiar for software engineers. If a connector doesn't exist our SDK makes it easy to build it.

[0] https://github.com/meltano/meltano

(disclaimer - I work at Meltano)

We currently don't do any process optimization on a per-stream basis when doing an extract. We have seen folks in the community running each tap separately for each stream which can speed it up. We've got an issue around this (Melturbo).

Meltano

I built my data pipeline to Extract some data from websites and CSV files, Load it into my database, and Transform it into a reporting-ready schema. I used Python and Pandas to extract and load some of the data and Meltano to load some additional supporting data. All of that data went into a PostgreSQL database hosted in the cloud on Azure where I then used dbt to create data models in the database optimized for reporting. Finally, I use Metabase to visualize the data. (whew! that's a lot of moving parts!)

I'm learning https://meltano.com/ right now, so am building custom Taps, mostly for fun. I'm enjoying it. I'm pulling in a variety of data from https://www.geonames.org/ and Canadian weather/climate data into BigQuery

https://meltano.com/ is ELT but I like it