ETL Frameworks

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.

Python library that facilitates the loading phase in ETL processes. Designed to simplify loading data into various data stores or processing systems.

Open-source transformation tool enabling data analysts and engineers to transform, test, and document data in the warehouse. Focuses on the transform part of ETL with SQL templating and Python scripting.

Lightweight Extract-Transform-Load (ETL) framework for Python 3.6+. Allows writing ETL scripts in pure Python, particularly suited for simple and straightforward ETL tasks.

Modern data pipeline tool focused on automating data preparation and feature engineering for machine learning. Streamlines the data transformation process in ETL workflows.