DuckDB: Intro & Basic Demo of Python DB-API & Relational API

Analytical SQL DBMS in Python

Tech Stack

Python 3,
DuckDB,
VsCode, Jupyter, GitHub

Project

Introducing DuckDB and execution of basic SQL queries and database manipulation

Benefits

DuckDB significantly speeds up database manipulation for datasets of a few terabytes. It integrates seamlessly with Python and various APIs, making it a preferred SQL tool across companies. Additionally, it enhances the functionality of analytical libraries such as Pandas, Polars, PyArrow, and NumPy. This is an asset tool for any involved data analyst.

Goals

Expanding and enhancing my SQL and DuckDB skills.

It's all in the notebooks:

Because everything is laid out and clearly written in the notebooks, I will not repeat any of that information here.

Please find these notebooks in these Github links below:

Part 1: Intro of DuckDB
You will understand what is DuckDB, why use it and when not to. You will come to understand why it is becoming increasingly popular.
Part 2: Demo use of the 2 APIs of choice: Python DB-API & Relation API
I stay within Python and show the power of DuckDB via these 2 APIs of choice for Data Analysts.

DuckDB reveals itself as an asset tool for any data analyst who wants to save time, save costs, and share work with other professionals that are non-python or non-analytics specialists.