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It simplifies the process of building and maintaining data pipelines by providing a standardized approach to defining and managing data processing workflows. Fabricks is battle-proven, used in production environments running thousands of jobs. 💪🚀\r\n\r\nCurrently, Fabricks is based on Azure **Databricks** and runs on Azure, utilizing Azure Blob Storage, Azure Table Storage, and Azure Queue Storage. Porting it to AWS or Google Cloud should not be a significant challenge. ☁️🔄\r\n\r\nAlthough Fabricks is primarily designed to run on **Databricks**, the code using Fabricks is highly portable. You'll predominantly write SQL-Select code, eliminating the need to manually write DDL/DML/Merge queries. In the future, we may add support for other platforms such as DuckDB or Open Source Spark. 🐍📊\r\n\r\n## Use Cases 🛠️\r\n- Data Ingestion using Python Notebooks, Jupyter-style\r\n- ETL using SQL-queries (should cover 99% of cases) or Notebooks\r\n- Data Distribution using Python Notebooks\r\n\r\nNo need for magic here. It's all your Data Lakehouse/Data Warehouse code in one place. Simple and great! ✨ You don't need expensive Delta Live Tables, ETL Tools, or DBT. It's basically just writing SQL Queries and letting Fabricks do the magic 🧙‍♂️. \r\n\r\n## About this repo 🕵️‍♂️\r\nWe're just getting started with open-sourcing Fabricks! There are many areas where we want to improve:\r\n- Implement testing in GitHub Actions 🧪👨‍💻\r\n- Decouple Spark dependencies where possible ⚡🔓\r\n- Migrate YAML parsing to Pydantic 📄🔄\r\n- Enhance documentation with more examples and best practices 📚💡\r\n- Develop a comprehensive getting started guide 🚀📘\r\n- Create a contribution guide for the open-source community 🤝🌐\r\n\r\n## More Information ℹ️\r\nSee [Fabricks Documentation](https://fabricks-framework.github.io/fabricks/)\r\n\r\n### Release Notes\r\n\r\nFor the latest releases and detailed changelogs, please visit the [Fabricks Releases page on GitHub](https://github.com/fabricks-framework/fabricks/releases).\r\n\r\n### Runtime Requirements\r\n\r\n[✔] `Fabricks 4.0.0` was successfully tested on Databricks Runtime `16.4 LTS`.\r\n\r\n[✔] `Fabricks 4.0.10` was successfully tested on Databricks Runtime `17.3 LTS`.\r\n\r\n## Related Projects 🔗\r\n- We use [odbc2deltalake](https://github.com/bmsuisse/odbc2deltalake) for extensive SQL Server data ingestion in a pre_run notebook. 🔌🏊‍♂️","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffabricks-framework%2Ffabricks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffabricks-framework%2Ffabricks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffabricks-framework%2Ffabricks/lists"}