Selection between BigQuery Compressed Storage vs Logical Storage pricing model

Google Cloud Data Analytics
1

Hi All,

I am currently evaluating the factors that could guide us to when to switch the default storage dataset model to the Compressed storage model (Physical). Based on the online documentation, there seems to be a forecasting model that approximates how much we could save if we switch to a compressed storage model. I would like to know if it is enough to see if the forecasted savings are good enough, and if we do have at least a 2x time active compression ratio, then we should enable a compressed storage model for the given dataset.

Are there any other parameters that we need to consider before switching to the Compressed storage model?

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Currently in BigQuery storage is billed on logical size , with compressed billing model billing would be based on actual physical storage which is compressed and lower in size than logical mostly. Compressed storage pricing allows you to only pay for data storage after it’s been highly compressed. With compressed storage pricing, you can reduce your storage costs while increasing your data footprint at the same time.

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