Summary

The article discusses how DuckDB can be used to reduce warehouse costs by enabling transpilation of SQL queries from traditional data warehouses like BigQuery to DuckDB. It introduces a feature called 'quack mode' in the lea data orchestrator, which allows users to run queries locally on DuckDB while still pulling necessary data from their existing warehouse. The author emphasizes the advantages of this approach in terms of cost efficiency and flexibility in data orchestration. Additionally, it touches on the integration of DuckDB with Iceberg for improved data management.

💭 Your Thoughts

My understanding is use DuckDB as a CTAS computation engine, read the data via a defined DAG in lea (from the BigQuery in the blog), then compute and output the data on the Object store. I’m using DuckDB in production but for serving the data via SQL. this is an interesting approach. The major reason to do this is for cost saving. But why not AWS Apache, or directly compute the data in BigQuery and output to object store?

Data Problems Addressed

Technologies Referenced