DuckDB is a Relational Database Management System (RDBMS) that supports the
Structured Query Language (SQL). It is designed to support Online Analytical Processing(OLAP), and it is well suited for performing data analytics.
Unlike traditional database systems where you need to install them, DuckDB requires no installation and works in-process. Because on this, DuckDB can run queries directly on Pandas data without needing to import or copy any data. Moreover, DuckDB uses vectorized data processing which makes it very efficient – internally the data are stored in columnar format rather than row-format (which is commonly used by databases systems such as MySQL and SQLite).In this workshop, you will learn how to use DuckDB to perform data analytics.
Topics:
- Use cases for DuckDB
- Creating a DuckDB database
– Creating tables
– Inserting Values
– Updating Values
– Deleting Values
– Retrieving Values
- Working with Pandas DataFrames
– Importing CSV files
– Registering Dataframes
– Joining dataframes
- Using Relations
– Setting alias
– Filtering
– Projection
– Aggregation
– Joining relations
- Using Tad – Tabular Data Viewer
– Installing Tad
– Viewing CSV files using Tad