DuckDB is a relatively new and explosively popular DBMS that is increasingly being adopted for analytical data workloads by data scientists, data analysts, data engineers, and software engineers. DuckDB is open source software that is made available under the permissive MIT license, making it friendly to both commercial and non-commercial applications alike. The non-profit DuckDB Foundation stewards the long-term health of the DuckDB project, and the development of DuckDB is supported by DuckDB Labs, which employs the project’s core contributors.
Topics covered :
• An Introduction to DuckDB,
• Loading Data into DuckDB, provides an exploration of DuckDB’s features, looking at how to load data into DuckDB from a range of formats and shapes, across CSV, JSON, and Parquet files.
• Data Manipulation with DuckDB, explores DuckDB’s powerful data wrangling capabilities.
• DuckDB Operations and Performance,
• DuckDB Extensions, introduces DuckDB’s extension system, which enables users to extend DuckDB’s functionality with useful features and capabilities that sit outside of the core DuckDB API.
• Semi-Structured Data Manipulation. This also included covering DuckDB’s strong support for working with JSON data.
• Setting up the DuckDB Python Client, sets up our Jupyter-Notebook-based IDE for working with DuckDB in Python and then unpacks the different ways to connect to DuckDB databases in Python.
• Exploring DuckDB’s Python AP
• Exploring DuckDB’s R API, explores the features of DuckDB’s R client.
• Using DuckDB Effectively, surveys some of DuckDB’s SQL enhancements and features that are designed to improve the experience of writing analytical queries.