Apache Airflow
Apache Airflow
Open-source platform for programmatically authoring, scheduling, and monitoring data pipelines.
About
Apache Airflow is an open-source workflow management platform for data engineering pipelines. It allows users to programmatically author, schedule, and monitor workflows, with tasks defined as Directed Acyclic Graphs (DAGs) in Python. Airflow is widely adopted by data engineers, data scientists, and MLOps teams for automating complex workflows, orchestrating machine learning tasks, and managing cloud-native operations. Teams look it up for MLOps, DataOps, Workflow Automation.
AWS Step Functions provides a serverless workflow orchestration service that competes with Apache Airflow's capabilities for defining and managing data pipelines, particularly within the AWS ecosystem.
Google Cloud Composer is a managed Apache Airflow service that directly competes by providing a fully managed environment for running Airflow workflows on Google Cloud.
Broadcom Automic Automation offers enterprise-grade workload automation and orchestration, competing with Apache Airflow in managing complex IT and data workflows across various systems.
Allstate, a large insurance organization, would benefit from Apache Airflow's ability to manage complex ETL, orchestration, and scheduling for data science and analytics functions, similar to how AbbVie uses it for clinical development and
US Foods, a major distribution organization, could leverage Apache Airflow to automate and manage its supply chain and logistics data pipelines, ensuring efficient data flow for operational insights.
NextEra Energy, a large utilities company, could use Apache Airflow to orchestrate data workflows related to energy consumption, grid management, and renewable energy operations.
Pinterest, a media organization with a significant user base, could utilize Apache Airflow to manage and automate its data pipelines for user engagement analytics, content recommendations, and ad targeting.
AbbVie, a life sciences organization, already uses Apache Airflow to operationalize pipeline orchestration for its Data Science and Analytics function, managing ETL, orchestration, and scheduling for clinical development and R&D analytics.
Buyer fit inferred by StartupHub from what Apache Airflow sells and public signals about each company. Only rows badged "already a customer" are confirmed relationships.
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“Apache Airflow has become the backbone of modern data orchestration. It schedules, monitors, and manages complex workflows across data pipelines, machine learning models, and ETL processes. But running Airflow in production is not a "set it…”
View on Reddit“Is Apache Airflow still the go-to tool for managing data pipelines?. Apache Airflow has been around for a while, but it still comes up constantly whenever teams talk about data orchestration, ETL pipelines, workflow automation, and producti…”
View on Reddit“Apache Airflow 3.2.0 is live. I think, it's time to start ETLs in Apache Airflow 3.2.0 . No more money to pay legacy ETL systems.”
View on Reddit“Apache Airflow 3.0 is here – and it’s a big one!. After months of work from the community, Apache Airflow 3.0 has officially landed and it marks a major shift in how we think about orchestration! This release lays the foundation for a more…”
View on Reddit“Apache Airflow best practices - AMA. We used to run airflow on a vertically scaled single instance. It was a nightmare. Given we run 100s of DAGs, we invested considerable amount of time to revamp. Here are a few learnings: Infrastructure A…”
View on Reddit“Apache Airflow sucks change my mind. I'm a Data Scientist and really want to learn Data Engineering. I have tried several tools like : Docker, Google Big Query, Apache Spark, Pentaho, PostgreSQL. I found Apache Airflow somewhat interesting…”
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