Amazon S3 Tables promised to eliminate the operational scaffolding of Apache Iceberg on S3 — automatic compaction, native REST catalog, managed snapshot lifecycle. Fourteen months after the re:Invent 2024 announcement, this is the enterprise practitioner assessment: what teams migrated from traditional S3 + Glue Catalog setups, the Lake Formation column masking gap that affects regulated workloads, and the migration decision framework for data engineering teams evaluating the switch.
Read more →Category: Cloud Engineering
Amazon S3 Tables & Apache Iceberg: Native Lakehouse in S3 — 14 Months Later
Amazon S3 Tables promised to eliminate the operational scaffolding of Apache Iceberg on S3 — automatic compaction, native REST catalog, managed snapshot lifecycle. Fourteen months after the re:Invent 2024 announcement, this is the enterprise practitioner assessment: what teams migrated from traditional S3 + Glue Catalog setups, the Lake Formation column masking gap that affects regulated workloads, and the migration decision framework for data engineering teams evaluating the switch.
Read more →Amazon Aurora DSQL in Production: What 15 Months Teaches Enterprise Architects
Aurora DSQL promised active-active multi-region SQL with no conflict resolution code. Fifteen months after the re:Invent 2024 announcement, this is the honest production assessment: what OCC delivers, where the feature gaps still bite, the migration blockers to audit before committing, and the cost model that makes it genuinely compelling for multi-tenant SaaS architectures.
Read more →