How DuckLake Simplifies Lakehouse Architecture ft. Jordan Tigani & Hannes Mühleisen

​Join MotherDuck CEO Jordan Tigani and DuckDB's Hannes Mühleisen for an in-depth discussion about DuckLake, the new lakehouse format that's rethinking how we handle metadata and open table formats. ​Discover what led to DuckLake's creation, how it differs from existing solutions, and what it means for the future of data architecture. ☁️🦆 Start using DuckDB in the Cloud for FREE with MotherDuck : https://hubs.la/Q02QnFR40 ➡️ Follow Us LinkedIn: https://linkedin.com/company/motherduck X/Twitter : https://twitter.com/motherduck Blog: https://motherduck.com/blog/ 00:00 Intro 00:33 What is DuckLake ? 02:37 Why Open Table Formats Matter 05:36 The Real Pain Point: Updates in Data Lakes 07:43 Storage Cost & Efficiency with Lakehouse Architecture 10:34 Aesthetic Frustrations with Iceberg 14:57 Is Iceberg the New Hadoop? 17:41 Iceberg's Problems Are Conceptual, Not Just Implementation 23:32 What Is DuckLake, Actually? 25:50 DuckLake = SQL Spec + Parquet + Database 29:41 Developer Simplicity: 3-Step DuckLake Setup 33:54 DuckLake vs Hive Metastore 35:40 High Frequency Updates & Snapshots in DuckLake 39:03 DuckLake at Petabyte Scale 42:37 Use Any Metadata Database (BigQuery, Postgres, etc.) 43:54 Early Feedback & Criticism ("Another Standard") 45:46 Vendors & Catalog Lock-in Concerns 47:13 Why So Few Iceberg Implementations Exist 49:04 MotherDuck's Plans for Hosting DuckLake 50:44 Q&A: Will Vendors Adopt DuckLake? 51:49 Why Avro Should Die 54:53 Just Use Parquet™ 55:14 Access Management in DuckLake 57:55 Why REST APIs Are the Wrong Fit 59:59 Closing Thoughts #duckdb #ducklake #iceberg #lakehouse #datalake #warehouse #icebergvsducklake