{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/629a6154b4e1e70012764c00/6988f792ba7d04f1d4c678af?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Mateusz Gienieczko | AnyBlox: A Framework for Self-Decoding Datasets | #69","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/629a6154b4e1e70012764c00/1770575805557-771355b7-9e70-4da5-a939-8aef80bdfb4f.jpeg?height=200","description":"<p>In this episode of Disseminate: The Computer Science Research Podcast, host Dr. Jack Waudby is joined by Mateusz Gienieczko, PhD researcher at TU Munich and co-author of the VLDB Best Paper Award winning paper AnyBlox.</p><p><br></p><p>They dive deep into a fundamental problem in modern data systems: why cutting-edge data encodings and file formats rarely make it from research into real-world systems — and how AnyBlox proposes a radical solution.</p><p><br></p><p>Mateusz explains the core idea of self-decoding data, where datasets ship with their own portable, sandboxed decoders, allowing any database system to read any encoding safely and efficiently. Built on WebAssembly, AnyBlox bridges the long-standing gap between database research and practice without sacrificing performance, portability, or security.</p><p><br></p><p>This episode is essential listening for database researchers, data engineers, system builders, and industry practitioners interested in the future of data formats, analytics performance, and making research matter in practice</p><p><br></p><p>Links:</p><ul><li>Paper: https://www.vldb.org/pvldb/vol18/p4017-gienieczko.pdf</li><li>GitHub: https://github.com/AnyBlox</li><li>Mat's Homepage: https://v0ldek.com/</li></ul>","author_name":"Jack Waudby"}