The JSON evolution with SQL Database
summary
Shows that Azure SQL can store and query large JSON payloads by loading Kaggle movie data and ~0.5M reviews (~1 GB) into tables, a hybrid table (columns + JSON) and a full JSON key/value row. Uses OPENJSON/CROSS APPLY and JSON_VALUE/JSON_QUERY/ISJSON to project arrays into rows, casts types and parses durations with a helper function, and demonstrates the slow memory-heavy join on a 1 GB JSON row. Recommends ingest with Data Factory or bulk copy, present via views, then denormalize into a heap and convert to clustered columnstore for 80% compression and fast analytics.
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chapters (8)
- 0:00Introduction
- 1:35Relational vs JSON approaches
- 15:07Demo setup and data ingestion
- 22:57Relational database limitations
- 32:33JSON integration in SQL
- 47:28Key-value storage experiment
- 51:22Takeaways and denormalization
- 59:45Summary and Q&A
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