The use case for pg_lakehouse is the following: You have historical data which you want to surface as a user-facing experience. Companies build their frontends

The use case for pg_lakehouse is the following: You have historical data which you want to surface as a user-facing experience. Companies build their frontends against Postgres, and needing to also build frontends against Snowflake/DuckDB/etc. is a lot harder to maintain than just keeping your frontend built against Postgres and use pg_lakehouse to query it. pg_lakehouse is not trying to replace data warehouses. Data warehouses are the best tool for internal analytics (i.e. a data analyst crunching large historical data to inform some business strategy decision). pg_lakehouse is designed for exposing historical data in user-facing analytics features (like a dashboard) with a good price-performance tradeoff. Thanks for your support :)