Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
-
Updated
Dec 5, 2024 - Python
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Workflow Engine for Kubernetes
Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code
PipelineAI
Build data pipelines, the easy way 🛠️
Docker Apache Airflow
Curated list of resources about Apache Airflow
DataSphereStudio is a one stop data application development& management portal, covering scenarios including data exchange, desensitization/cleansing, analysis/mining, quality measurement, visualization, and task scheduling.
Elyra extends JupyterLab with an AI centric approach.
A series of DAGs/Workflows to help maintain the operation of Airflow
Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.
Dynamically generate Apache Airflow DAGs from YAML configuration files
More than 2000+ Data engineer interview questions.
Example end to end data engineering project.
A Data Engineering & Machine Learning Knowledge Hub
🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
Personal Data Engineering Projects
Run your dbt Core projects as Apache Airflow DAGs and Task Groups with a few lines of code
Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.
Add a description, image, and links to the airflow topic page so that developers can more easily learn about it.
To associate your repository with the airflow topic, visit your repo's landing page and select "manage topics."