Embracing Schema Drift: Seamless Parquet Querying in Tanzu Greenplum, No Matter How Your Data Changes

A data lake is a living archive and not a static snapshot. Files written in January rarely look like those written in December. As products evolve and businesses change, columns are inevitably added, renamed, dropped, and reordered. The critical question is: does your query engine evolve with them? Unlike traditional databases, data lakes lack a … Continued

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