dbt-documentor
Mage
dbt-documentor | Mage | |
---|---|---|
1 | 79 | |
19 | 8,264 | |
- | 1.3% | |
3.5 | 9.5 | |
about 2 years ago | 7 days ago | |
F# | Python | |
MIT License | 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.
dbt-documentor
Mage
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Wk 3 Orchestration: MLOPs with DataTalks
Here, we use the free Mage Ai orchestration tool.
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25 Open Source AI Tools to Cut Your Development Time in Half
Mage AI is a data transforming and integrating framework that allows data scientists and ML engineers to build and automate data pipelines without extensive coding. Data scientists can easily connect to their data sources, ingest data, and build production-ready data pipelines within Mage notebooks.
- FLaNK AI-April 22, 2024
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A mage on the Hero’s Journey: a fantasy epic on how a startup rose from the ashes
In the coming years, Mage will create a cooperative experience so that developers can build data pipelines with their team and level up together. After that journey, Mage will go on an epic quest to create the 1st open world community experience in the data universe.
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Data sources episode 2: AWS S3 to Postgres Data Sync using Singer
Link to original blog: https://www.mage.ai/blog/data-sources-ep-2-aws-s3-to-postgres-data-sync-using-singer
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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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Mage Battlegrounds: Craft insights from real-time customer behavior analysis
You're invited to participate in the very first Mage Battlegrounds: Craft insights from real-time customer behavior analysis, a 24-hour virtual hackathon hosted by Shashank Mishra! This data engineering competition will take place on Saturday, April 15, 2023 beginning at 11am (PST). This will be a global event open to all participants who register.
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Looking for an open-source project
Try this feature: https://github.com/mage-ai/mage-ai/issues/1166
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Daskqueue: Dask-based distributed task queue
Seeing if we can use it in https://github.com/mage-ai/mage-ai
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Data Pipeline on a Shoestring
That being said there’s a solid family of services just breaking ground that make the local pipeline deployment easier (check out https://www.mage.ai, which does have a clear path to cloud deployment of locally developed pipes, it just isn’t well documented yet, and also https://www.neuronsphere.io - which doesn’t have a public solution YET (they’re internally testing an alpha) but they built a cloud deployable solution for their paying customers and working to release one for freemium use)
What are some alternatives?
optimus - Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.
dagster - An orchestration platform for the development, production, and observation of data assets.
dbt-data-reliability - dbt package that is part of Elementary, the dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
vscode-dvc - Machine learning experiment tracking and data versioning with DVC extension for VS Code
F# Formatting - F# tools for generating documentation (Markdown processor and F# code formatter)
astro-sdk - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.