SQLite as an embedded database is known by everyone — easy to integrate into any application, it's the most widely used database in the world. DuckDB is also an embedded database, but with a focus on analytical queries rather than transactional workloads. Today, DuckDB has evolved into a blazingly fast query engine that runs almost everywhere. This opens up new architectural possibilities for building data-driven applications — especially when analytics need to be delivered directly to end users through interactive reports, dashboards, or exploratory tools. In this workshop, we'll gain hands-on experience with using duckdb, to show how to build fast and lean data applications with DuckDB. We'll explore scenarios including browser-based analytics powered by WebAssembly, serverless function processing data from cloud storage, and embedded analytics in traditional applications. We'll also examine the architectural implications: how embedded OLAP changes data architectures by bringing compute closer to the data, enabling 1.5-tier and cache-layer patterns that eliminate the need for separate analytics infrastructure. Attendees will learn what DuckDB is and how it works, how it differs from other embedded databases, and how to use it to build data-driven applications that go well beyond the notebook.
canela Workshop
€50
Max. Attendees: 30
Free registration for Early Camarón & Bokeron ticket holders and a discount
for all others
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.