airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

🔮 Build multimodal AI services via cloud native technologies

Workflow engine for Kubernetes

Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code

PipelineAI Kubeflow Distribution

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

⚡ Data quality management for SQL, Spark, and Pandas-accessible data

An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.

Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.

A Data Engineering & Machine Learning Knowledge Hub

Dynamically generate Apache Airflow DAGs from YAML configuration files

Example end to end data engineering project.

Yet another cron alternative with a Web UI, but with much more capabilities. It aims to solve greater problems.

Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.

The User-Community Airflow Helm Chart is the standard way to deploy Apache Airflow on Kubernetes with Helm. Originally created in 2018, it has since helped thousands of companies create production-ready deployments of Airflow on Kubernetes.