DuckDB: Beyond the Notebook

Key Takeaways

• Run DuckDB queries directly against CSV, JSON, and Parquet files stored locally or in cloud object storage.
• Build a browser-based analytics application powered by DuckDB and WebAssembly, without requiring a backend server.
• Use DuckDB as an embedded analytics engine inside serverless functions for fast, lightweight data processing.
• Discover modern architectural patterns such as 1.5-tier applications and cache-layer designs enabled by embedded OLAP.
• Leave with practical code examples you can immediately adapt for your own projects.

Target Audience

• Software engineers building or maintaining data-driven applications.
• Data engineers looking to simplify analytics pipelines and tooling.
• Developers interested in embedded analytics and modern data architectures.
• Anyone curious about using DuckDB beyond traditional data warehouse workflows.

Requirements

• Python 3.11 or newer installed.
• uv installed for Python package management.
• An IDE or code editor suitable for Python development.
• DuckDB CLI installed on your machine.
• Basic knowledge of SQL and Python.
• JavaScript or TypeScript familiarity is helpful but not required.