Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows

Analyze and transform data efficiently with DuckDB, a versatile, modern, in-process SQL database

Key Features

Use DuckDB to rapidly load, transform, and query data across a range of sources and formats

Gain practical experience using SQL, Python, and R to effectively analyze data

Learn how open source tools and cloud services in the broader data ecosystem complement DuckDB’s versatile capabilities

Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionDuckDB is a fast in-process analytical database. Getting Started with DuckDB offers a practical overview of its usage. You'll learn to load, transform, and query various data formats, including CSV, JSON, and Parquet. The book covers DuckDB's optimizations, SQL enhancements, and extensions for specialized applications. Working with examples in SQL, Python, and R, you'll explore analyzing public datasets and discover tools enhancing DuckDB workflows. This guide suits both experienced and new data practitioners, quickly equipping you to apply DuckDB's capabilities in analytical projects. You'll gain proficiency in using DuckDB for diverse tasks, enabling effective integration into your data workflows.What you will learn

Understand the properties and applications of a columnar in-process database

Use SQL to load, transform, and query a range of data formats

Discover DuckDB's rich extensions and learn how to apply them

Use nested data types to model semi-structured data and extract and model JSON data

Integrate DuckDB into your Python and R analytical workflows

Effectively leverage DuckDB's convenient SQL enhancements

Explore the wider ecosystem and pathways for building DuckDB-powered data applications

Who this book is forIf you’re interested in expanding your analytical toolkit, this book is for you. It will be particularly valuable for data analysts wanting to rapidly explore and query complex data, data and software engineers looking for a lean and versatile data processing tool, along with data scientists needing a scalable data manipulation library that integrates seamlessly with Python and R. You will get the most from this book if you have some familiarity with SQL and foundational database concepts, as well as exposure to a programming language such as Python or R.