Apache Iceberg V3 Deletion Vectors Explained: Faster, Cheaper Row-Level Deletes

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Deleting individual rows in a data lakehouse is technically complex because object stores like Amazon S3 treat files as immutable — they can be written and read but never edited in place. Apache Iceberg V2 addressed this with 'delete files,' a merge-on-read mechanism that logged which rows to ignore rather than rewriting entire data files. While this made row-level changes practical, it shifted processing costs to readers and degraded performance under heavy workloads. Iceberg V3 introduced 'deletion vectors,' a more efficient approach that improves read performance and scales better under pressure. The shift from delete files to deletion vectors represents a significant architectural refinement that expands the range of workloads a lakehouse can reliably support.

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