Curbing the cost of cloud analytics and data warehousing

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Curbing the cost of cloud analytics and data warehousing
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On the hunt for price performance gains that Amazon can pass on to its customers

Information wants to be free. It also tends to be expensive - especially when you have to process it. As we struggle to squeeze more insights out of our data, the race is on to reduce the computational cost involved. And the cloud is helping to increase the performance of the gargantuan data warehouses needed to drive new insights, without breaking the bank.

Decoupling compute from storage enabled customers to boost their data processing capabilities without paying for unnecessary data storage. The Redshift performance team focuses on increasing the performance of the compute and storage infrastructure, with the improvements tailored to show up on budgets rather than benchmarks.

Amazon engineers developed a new way to manage compressed string data on disk. Vectorizing the algorithms that read string compression encodings permitted CPU-efficient scans over compressed dictionary-encoded string columns. This accelerated the processing of multiple strings by up to sixty times for queries processing large amounts of string data, Gromoll says.began using Amazon Redshift Serverless in 2022 in a bid to improve its use of marketing analytics to increase game sales.

Automatic workload management is set up automatically in Redshift. Amazon made a serverless option for Redshift available in July 2022, joining its provisioned Redshift deployment mechanisms. "So you can really dial in exactly the performance and cost you want without having to pay for more compute than you need - you don't have to double your warehouse if you just need a little bit more compute." Gromoll adds.The impact of these price performance improvements grows with the volume of data that customers are processing in Redshift - and there are some very large users indeed.

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