SQream Platform
GPU Powered Data & Analytics Acceleration
Enterprise (Private Deployment) SQL on GPU for Large & Complex Queries
Public Cloud (GCP, AWS) GPU Powered Data Lakehouse
No Code Data Solution for Small & Medium Business
Scale your ML and AI with Production-Sized Models
By Noa Attias
Definition and Overview
Apache Airflow is an open-source platform designed for workflow automation and scheduling, allowing users to programmatically author, schedule, and monitor workflows. Originating at Airbnb in 2014, Airflow has become a pivotal tool in data engineering, supporting diverse tasks from ETL processes to machine learning model training.
Core Features and Benefits
Use Cases
Airflow is widely employed for data pipeline orchestration, batch processing, and automating machine learning workflows, among other applications. Its scalability and versatility make it a standard in managing complex data processing tasks.
Conclusion
Apache Airflow stands out for its ability to orchestrate complex workflows, backed by a strong community and a flexible architecture. Its use of DAGs for task scheduling and monitoring offers a powerful tool for data engineers and scientists alike.