Is it possible to store semi-structured or unstructured data in Amazon Redshift?
💡 Model Answer
Amazon Redshift supports semi‑structured data through the SUPER data type, which can store JSON, XML, AVRO, Parquet, and other formats. You can load data into a SUPER column using COPY from S3 or INSERT statements, and query it with SQL functions like JSON_EXTRACT_PATH_TEXT, JSON_VALUE, or the newer JSON_TABLE syntax. For truly unstructured data (e.g., plain text, images), Redshift typically stores it as VARCHAR or as an external table that points to S3 objects. Redshift Spectrum can also query data stored in S3 without loading it into the warehouse, allowing you to keep raw files in a data lake while still using Redshift for analytics. Thus, while Redshift is primarily a structured warehouse, it has built‑in mechanisms to ingest, store, and query semi‑structured data, and can reference unstructured files via external tables.
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