Lakehouse Architecture (Databricks Iceberg Delta)
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Stage One — What the Lakehouse Actually Solves
The Problem With Warehouse and Lake Alone
Preview
One Copy of the Data, Many Engines
Choosing Between the Formats
3 lessons
Stage Two — How Table Formats Work Underneath
Metadata Files and Atomic Commits
Time Travel Snapshots and Rollback
Schema and Partition Evolution
3 lessons
Stage Three — Layout and Performance
Partitioning Done Properly
Compaction Clustering and File Sizing
Statistics Pruning and Query Behaviour
3 lessons
Stage Four — Medallion Layers and Modelling
The Bronze Silver Gold Pattern
Modelling in the Gold Layer
Deletes Updates and Regulatory Erasure
3 lessons
Stage Five — Streaming and Incremental Processing
Streaming Into Lakehouse Tables
Incremental Reads and Change Feeds
Backfills Late Data and Correctness
3 lessons
Stage Six — Governance Cost and Operations
Catalogs and Access Control
Cost Control on the Platform
Operating the Platform and Career Path
3 lessons
Stage One — What the Lakehouse Actually Solves
One Copy of the Data, Many Engines
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