Haralampos Gavriilidis | SheetReader: Efficient spreadsheet parsing
Failed to add items
Add to basket failed.
Add to Wish List failed.
Remove from Wish List failed.
Follow podcast failed
Unfollow podcast failed
Haralampos Gavriilidis | SheetReader: Efficient spreadsheet parsing
-
Narrated by:
-
By:
About this listen
In this episode of the DuckDB in Research series, Harry Gavriilidis (PhD student at TU Berlin) joins us to discuss Sheet Reader — a high-performance spreadsheet parser that dramatically outpaces traditional tools in both speed and memory efficiency. By taking advantage of the standardized structure of spreadsheet files and bypassing generic XML parsers, Sheet Reader delivers fast and lightweight parsing, even on large files. Now available as a DuckDB extension, it enables users to query spreadsheets directly with SQL and integrate them seamlessly into broader analytical workflows.
Harry shares insights into the development process, performance benchmarks, and the surprisingly complex world of spreadsheet parsing. He also discusses community feedback, feature requests (like detecting multiple tables or parsing colored rows), and future plans — including tighter integration with DuckDB and support for Arrow. The conversation wraps up with a look at Harry’s broader research on composable database systems and data interoperability, highlighting how tools like DuckDB are reshaping modern data analysis.
Hosted on Acast. See acast.com/privacy for more information.