Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
- airflow
- apache
- apache-airflow
- python
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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
An orchestration platform for the development, production, and observation of data assets.
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Translated【A common used C++ & Python DAG framework】 A general-purpose, third-party-dependency-free, cross-platform parallel computing framework based on flow graphs, listed in awesome-cpp. Welcome to star & fork & discuss
Simple but powerful DAG scheduler and dashboard
Free and open source schema versioning and database migration made natively with .NET/6. NEW THIS MAY 2022! v1.3.15 released!
Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching
Distributed batch data processing framework
Reverse ETL for the code-first data stack
Distributed, Scalable, Fault-Tolerant, Minimalistic Workflow Engine - No DAGs, No YAML, No Cumbersome Diagrams, Just Code
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