Reference architectures for Amazon Redshift data warehouses

on YouTube ↗22m

" summary

Shows how Amazon Redshift queries S3 data in place with Redshift Spectrum to keep warm data local and cold data in a lake house, uses Federated Query to run near-live queries against Aurora/RDS, exposes cross-cluster data sharing so producer clusters publish schemas consumers query with no copies, and offers a RESTful Data API for app access. Reference architectures include producer/consumer clusters, isolated tenant clusters that share specific tables for ML training, and data-as-a-service patterns for internal or external subscribers.

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" chapters (11)

1. 0:00Introduction
2. 1:23Data sharing: What's the idea?
3. 2:22Data sharing: Common business use cases
4. 3:46Data sharing: Common starting scenario
5. 6:51Data sharing: Common architecture goals
6. 8:36Amazon Redshift lake house
7. 10:52Amazon Redshift Spectrum overview
8. 14:00Amazon Redshift federated query
9. 15:27Amazon Redshift data sharing
10. 17:25Amazon Redshift Data API
11. 18:08Reference architecture

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