Modern data pipeline tool focused on automating data preparation and feature engineering for machine learning. Streamlines the data transformation process in ETL workflows.
Powerful Python library for data manipulation and analysis, offering DataFrame structures for efficient data cleaning, transformation, and analysis. Often used in the transform phase of ETL processes.
Python package specifically designed for ETL tasks, offering tools for data extraction, transformation, and loading. Suitable for simpler, script-based ETL processes.
Python API for Apache Spark, enabling scalable and efficient data processing. Particularly useful for ETL processes involving large datasets that need parallel processing across a cluster.