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Building an Open, Multi-Engine Data Lakehouse with S3 and Python
Run Python data apps reliably in production
A week later, Motherduck photo-bombed Databrick's own Summit by sending a platoon of duck-costumed people to Moscone Center, carrying signs including "Big Data is Dead" and "Single Machines Rule." We also caution against using Polars' "feature" to access Iceberg tables directly, circumventing a catalog unless you are doing this in development, only to read data, or are the only user of the lakehouse. Every change operation on data or schema (Inserts, Deletes, Updates, or adding/modifying columns) of a table will result in a new metadata file, and we need a catalog service to coordinate all of that.
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