![]() Compute costs are $0.00056 per second for each credit consumed on Snowflake Standard Edition, while the Snowflake Enterprise Edition (which includes customer-managed encryption keys and other security-hardened features and enables HIPAA and PCI compliance) costs $0.0011 per second for each credit consumed. All charges are usage-basedįor example, in the United States, Snowflake storage costs begin at a flat rate of $23 USD per compressed TB of data stored, averaged across the days in a month. ![]() Storage costs benefit from automatic compression of all data stored, and the total compressed file size is used to calculate the storage bill for an account. The charge for storage is based on the number of bytes stored per month, as well as the cost of moving data across regions or clouds that is passed on by the cloud vendor. Compute cluster usage time or serverless operations have a rate of credits consumed, and all compute charges are billed based on real, rather than predicted or estimated, usage-down to the second. Credits have a pricing rate depending on the edition used: standard, enterprise, or business-critical, each of which comes with a different list of features. The charge for compute is based on the number of credits used to run queries or perform a service, such as loading data with Snowpipe. Snowflake’s pricing model is primarily based on two consumption-based metrics: usage of compute and of data storage. This post describes how customers can use these features to strike the balance they need between flexibility and control. Snowflake balances the power of true cloud elasticity with clear visibility into usage and spend, monitoring and sending notifications when resource usage is higher than expected, and offering strong cost controls to shut off usage when caps are hit. This type of flexibility is powerful, but with this power comes risk-will spikes in demand lead to runaway spending? What’s more, users have an almost unlimited scale data repository that can be queried by a multitude of fully isolated compute clusters, allowing them to run concurrent workloads without negatively impacting each other, even when some of those workloads see big spikes in activity. Whether this demand is predictable or highly variable, the system can flex bigger or smaller to deliver results for key data workloads, while never carrying more capacity than needed. The Snowflake Data Cloud has near instant elasticity, allowing customers to scale up and down to meet demand. It has been updated to reflect currently available products, features, and functionality. PLEASE NOTE: This post was originally published in 2018.
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