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This article explores how Databricks Lakebase's copy-on-write database branching enables evolutionary database design practices that were previously aspirational, revisiting methodologies from the 2003 Evolutionary Database Design essay.
•Lakebase decouples compute and storage layers, using S3 for data storage and separate Postgres engines for computation
•Copy-on-write branching creates one-second, zero-storage-at-creation database branches regardless of parent size, making per-developer and per-PR databases practical
•The architecture removes previous constraints on five of the original seven evolutionary database design practices, particularly enabling everybody to get their own database instance
•GitHub Actions workflows automate per-PR branch creation, schema diff posting as PR comments, and branch cleanup on merge
•New capabilities emerge including destructive testing with zero blast radius, A/B variant database prototyping, and async DBA review of schema changes
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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