DRAFT - IN PROGRESS
A Guide for Data scientists, data engineers, data analysts, and Python developers seeking to leverage DuckDB for efficient data processing and analysis.
Table of Contents
Chapter 1: Introduction to DuckDB: The Embedded Analytical Revolution
To introduce DuckDB as a powerful embedded analytical database and explain its relevance in modern data engineering, highlighting its advantages over traditional systems.
- 1.1 The Evolution of Analytical Databases
- From OLTP to OLAP: A historical perspective
- Limitations of traditional data warehouses for real-time analytics
- The rise of embedded analytical databases
- 1.2 DuckDB's Architecture and Design Principles
- Columnar storage and vectorized query execution
- Embedded architecture: Bringing the database to the data
- Zero-copy data access and in-process analytics
- Concurrency and multi-threading model
- 1.3 DuckDB vs. Traditional Database Systems
- Comparing DuckDB to PostgreSQL, MySQL, and SQLite
- Use cases where DuckDB excels: Local analytics, data science, and prototyping
- Trade-offs and limitations of DuckDB
- DuckDB's Role in Serverless Architectures
- 1.4 Installation and Setup in Python Environments
- Installing the
duckdb
Python package
- Setting up a basic DuckDB connection
- Verifying the installation and exploring the DuckDB shell
Chapter 1 Draft
Chapter 2: Core Concepts: Connecting to DuckDB and Executing SQL
To establish a solid understanding of core DuckDB concepts, including the SQL interface, connection management, and basic querying.
- 2.1 Establishing Database Connections
- Creating in-memory databases
- Creating and managing persistent databases on disk
- Choosing the right storage mode for your use case
- 2.2 Executing SQL Queries from Python
- Using
.sql()
for query execution (preferred method)
- When to use
.execute()
for parameter binding
- SQL dialect and supported features
- Understanding DuckDB's SQL extensions
- 2.3 Basic Data Definition Language (DDL)
- Creating tables and defining schemas
- Choosing appropriate data types
- Basic schema design principles
- 2.4 Basic DuckDB API Usage
- Fetching query results
- Parameter binding and prepared statements
- Error handling and exception management
Chapter 2: Core Concepts: Connecting to DuckDB and Executing SQL