High-volume Data Streaming and Storage
summary
Covers event-driven architectures and strategies for storing very large datasets when traditional databases don’t fit, focusing on how storage formats (partitionability, reprocessing ability, compression, space use) affect processing. Compares storing data in multiple non-relational formats versus relational storage when query patterns are known, and applies these ideas to time series, web event capture, transactional data and data lakes.
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