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How AWS S3 Tables redefine data storage and analytics [Video]

Data storage is shifting from static to dynamic with Amazon Web Services Inc.’s introduction of AWS S3 Tables. This move reflects broader industry trends toward open-table formats prioritizing flexibility and interoperability.

S3 Tables enable customers to work with mutable, structured query language-like datasets, a significant change from the read-only nature of Apache Parquet files, according to Andy Warfield (pictured), vice president and distinguished engineer at AWS.

“On the Iceberg side, the distinction between traditional Parquet and the OTFs is that it takes what was basically read-only tables … and makes them mutable,” Warfield said. “It brings them closer to being a more conventional SQL table. That is becoming a primitive in S3, so you’ll be able to create a table bucket, we call it, create a table inside it — it gets its own endpoint. It’s a first-class resource, which means you can set policy.”

Warfield spoke with theCUBE Research’s Dave Vellante and John Furrier for theCUBE’s “Cloud AWS re:Invent coverage

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