Awesome Apache Airflow
Section: Vital links · (latest stable release 1.10.12)
Entry
Appears in 13 awesome lists
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
Section: Vital links · (latest stable release 1.10.12)
Section: Tools · A platform to programmatically author, schedule, and monitor workflows.
Section: Workflow · A system to programmatically author, schedule, and monitor data pipelines.
Section: Miscellaneous Tools · Platform to programmatically author, schedule, and monitor workflows
Section: Workflow Management/Engines · "Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
Section: Open Source Projects · Platform to author, schedule, and monitor workflows.
Section: Workflow Engine · Platform for programmatically creating, scheduling, and monitoring workflows, ideal for managing complex data pipelines.
Section: 1. Core Frameworks & Libraries · Platform to programmatically author, schedule, and monitor workflows. Industry-standard orchestration for data pipelines and ML workflows with 500+ integrations. Apache 2.0 licensed.
Section: Data Pipeline · Data Pipeline framework built in Python, including scheduler, DAG definition and a UI for visualisation.
Section: Data Science and Analytics · Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Section: Airflow (35 · 48K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 · (👨💻 4.7K · 🔀 18K · 📦 20K):
Section: Workflows · Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Section: Job Schedulers · Airflow is a platform to programmatically author, schedule and monitor workflows.
Python module for building complex pipelines of batch jobs. Handles dependency resolution, workflow management, visualization, and Hadoop integration. Built at Spotify and battle-tested in production. Apache 2.0 licensed.
Cloud-native orchestration platform for developing and maintaining data assets including ML models. Declarative programming model with integrated lineage and observability. Apache 2.0 licensed.
Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.
| Python | - A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.
is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to…
Unified analytics engine for large-scale data processing. In-memory cluster computing with high-level APIs in Python, Scala, Java, and R. Powers MLlib for distributed machine learning and Structured Streaming for real-time data. Apache 2.0 licensed.
Event-driven orchestration and scheduling platform for mission-critical workflows. Infrastructure-as-Code approach with declarative YAML, Git version control integration, and hundreds of plugins for data pipelines and ML workflows. Apache 2.0 licensed.
Stream processing framework with powerful batch and streaming capabilities. High-throughput, low-latency runtime with exactly-once processing guarantees. Ideal for real-time AI inference pipelines and event-driven ML applications. Apache 2.0 licensed.