full image - Repost: Separating Storage and Compute for Transaction and Analytics (from Reddit.com, Separating Storage and Compute for Transaction and Analytics)
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Separation of storage and compute is an important capability of most cloud native databases. Being able to scale compute independently from storage allows for cost savings as well as improved performance and elasticity. For example, operational databases such as Amazon Aurora and Azure Hyperscale have introduced separate log and storage services that do the work of making the log durable as well as some log maintenance work that would typically be done by the database engine itself. The result is lower network and disk utilization to provide high availability and durability of data. Cloud data warehouses (DWs) such as Snowflake and Amazon Redshift write data out to blob storage, keeping only hot data cached on local disks to be used by queries. This allows for databases larger than local disk and for compute to be quickly added or removed by pulling data from blob storage. You can read more about it in this link.
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