Apache Airflow Or Apache Beam For Data Processing And Job Scheduling
Answer : The other answers are quite technical and hard to understand. I was in your position before so I'll explain in simple terms . Airflow can do anything . It has BashOperator and PythonOperator which means it can run any bash script or any Python script. It is a way to organize (setup complicated data pipeline DAGs), schedule, monitor, trigger re-runs of data pipelines, in a easy-to-view and use UI. Also, it is easy to setup and everything is in familiar Python code. Doing pipelines in an organized manner (i.e using Airflow) means you don't waste time debugging a mess of data processing ( cron ) scripts all over the place. Apache Beam is a wrapper for the many data processing frameworks (Spark, Flink etc.) out there. The intent is so you just learn Beam and can run on multiple backends (Beam runners). If you are familiar with Keras and TensorFlow/Theano/Torch, the relationship between Keras and its backends is similar to the relationship between Beam and its...