castled
dagster
| castled | dagster | |
|---|---|---|
| 12 | 46 | |
| 316 | 10,274 | |
| - | 2.7% | |
| 9.9 | 10.0 | |
| about 2 years ago | 4 days ago | |
| Java | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
castled
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Data pipeline suggestions
Reverse ETL: Grouparoo, Castled
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
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Launch HN: Castled Data (YC W22) – Open-Source Reverse ETL
Thanks. We also have a subscription based hosted solution hosted at https://castled.io
- Castled - an open source reverse ETL solution that helps you to periodically sync the data in your db/warehouse into sales, marketing, support or custom apps without any help from engineering teams
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Castled.io is the fastest Reverse ETL platform till date
Castled is 6x to 13x faster than other Reverse ETL platforms like Census and Hightouch! The project is open source.
- Castled is an open source reverse ETL solution that helps you to periodically sync the data in your warehouses and databases to sales, marketing, support or custom apps without any help from engineering teams
- Castled – Reverse ETL
dagster
- Experience with Dagster.io?
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Dagster tutorials
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.
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The Dagster Master Plan
I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured
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What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
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The Why and How of Dagster User Code Deployment Automation
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.
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Best Orchestration Tool to run dbt projects?
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.
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dbt Cloud Alternatives?
Dagster? https://dagster.io
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What's the best thing/library you learned this year ?
One that I haven't seen on here yet: dagster
- Anyone have an example of a project where a handful of the more popular Python tools are used? (E.g. airbyte, airflow, dbt, and pandas)
- Can we take a moment to appreciate how much of dataengineering is open source?
What are some alternatives?
lightdash - Self-serve BI to 10x your data team ⚡️
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
X-Road - Source code of the X-Road® data exchange layer software
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
datahelix - The DataHelix generator allows you to quickly create data, based on a JSON profile that defines fields and the relationships between them, for the purpose of testing and validation
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
monosi - Open source data observability platform
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
MLflow - Open source platform for the machine learning lifecycle
projects - Sample projects using Ploomber.
meltano