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I used to explain AWS Aurora as "write as if it is data guard / read as if it is RAC". Really nice to read analysis on on Aurora "The log is the database" architecture. I'll add a few immediate subjective opinions on itπŸ‘‡
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Based on #AlloyDB's and #AmazonAurora's approach, some of us at #Oracle were asked about the usefulness of applying redo in the storage tier. These are some of our thoughts: blogs.oracle.com/maa/post/about /cc @dbinmemory, @ashishray
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Big difference between AWS Aurora read replicas and Oracle Active Data Guard queries: when you add the cache invalidation arrows onto the Aurora architecture diagram, it quickly looks like a monolithic database spaghetti plate over multiple instances
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>> the same idea has been picked up by two primarily cloud vendors simultaneously Not really simultaneously. GCP is a follower here. And is an open-source newcomer. Same idea of separating compute and storage but different times.
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>> Both solutions send the WAL directly to the read replicas, which amplifies writes Not really. WAL is sent to storage. 6 mirrors across 3 AZs. This is the write amplification, but for HA with q quorum of 4. Then read replicas on top, plus cache invalidation.
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Note that this (Aurora & AlloyDB) apply to PostgreSQL with full-row copy on any update and full page logging, on cloud providers where inter-AZ is not free. Oracle has optimized in-place updates, and free inter-AD network cost. Main reason for Aurora was the write cost
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OK I need to look at it again πŸ™ Do you mean 1. When not logging the full page and 2. With HOT updates then WAL record holds only the new value? Or in more general cases?
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See commit a3115f0d9e, which added the update WAL optimization back in 2014. It's unrelated to FPWs. The optimization applies to HOT and non-HOT updates, though in the case of non-HOT it only works when the update won't move the new version to another page.
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