Tag Archives: Data Lakehouse

From SCD2 Bronze to a Non-SCD Silver Layer in Other Tech (Iceberg, Hudi, BigQuery, Fabric)

Modern data platforms consistently separate historical truth from analytical usability by storing full SCD2 history in a Bronze layer and exposing a simplified, current-state Silver layer. Whether using Apache Iceberg, Apache Hudi, Google BigQuery, or Microsoft Fabric, the same pattern applies: Bronze preserves immutable, auditable change history, while Silver removes temporal complexity to deliver one row per business entity. Each platform implements this differently, via snapshots, incremental queries, QUALIFY, or Delta MERGE, but the architectural principle remains universal and essential for regulated environments.

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Databricks vs Snowflake vs Microsoft Fabric: Positioning the Future of Enterprise Data Platforms

This article extends the Databricks vs Snowflake comparison to include Microsoft Fabric, exploring the platforms’ philosophical roots, architectural approaches, and strategic trade-offs. It positions Fabric not as a direct competitor but as a consolidation play for Microsoft-centric organisations, and introduces Microsoft Purview as the governance layer that unifies divergent estates. Drawing on real enterprise patterns where Databricks underpins engineering, Fabric drives BI adoption, and functional teams risk fragmentation, the piece outlines the “Build–Consume–Govern” model and a phased transition plan. The conclusion emphasises orchestration across platforms, not choosing a single winner, as the path to a governed, AI-ready data estate.

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