Nitin Jadhav

pg_duckdb in Action: Accelerating Analytics on Azure Database for PostgreSQL

local CEST (Livestream 4)

If your analytics workflow starts with exporting data from Postgres, you’re not alone. Many teams build ETL pipelines just to answer questions about data that already lives in Postgres. But what if you didn’t have to move it at all? With pg_duckdb, you can run fast, columnar-style analytical queries inside Postgres without setting up a separate warehouse, a sync process, or another system to manage.

In this talk, I’ll walk through how pg_duckdb works, what it’s good at, and where it fits into real-world workflows. The demo will showcase pg_duckdb installed on Azure Database for PostgreSQL, where I’ll run analytical queries over existing tables and query Parquet files directly from object storage—without loading them into Postgres first.

It’s not a full replacement for a data warehouse, but in many cases, it’s a faster, simpler path to the answers your team needs—right from the database you already use. Attendees will learn how pg_duckdb works, how to use it effectively, and how to speed up analytics without extra tools or data movement. You’ll leave with practical tips and real examples you can apply right away.