How Usage-Based Pricing Delivers a Budget-Friendly Cloud Data Warehouse

April 11, 2018 Michael Nixon

When you have budgets and business plans you need to stick to, you want clear pricing when operating your cloud data warehouse. However, it can be a frustrating task to understand how some cloud data warehouses charge for services. Each vendor has its own pricing model. Users expect differences. However, it’s more about the hidden charges, quotas and other penalties that are frustrating.

Here are just some of the ways Snowflake helps you to manage your data warehouse budget easily, cost-effectively and efficiently.

A simple data warehouse pricing model

Snowflake’s pricing model includes only two items: the cost of storage and the cost of compute resources consumed. The charge for storage is per terabyte, compressed, per month. The charge for compute is based on the processing units, which we refer to as credits, consumed to run your queries or perform a service (for example, Snowpipe data loading). Compute charges are billed on actual usage, per second. All of our Snowflake editions and pricing details can be found here on our website.   

All charges are usage-based

As examples, using the US as a reference, Snowflake storage costs can begin at a flat rate of $23/TB, average compressed amount, per month accrued daily. Compute costs $0.00056 per second, per credit, for our Snowflake On Demand Standard Edition. Our Snowflake On Demand Enterprise Sensitive Data Edition (which includes HIPAA compliance, PCI compliance, customer managed encryption keys and other security hardened features) is $0.0011 per second, per compute credit.

Clear and straightforward compute sizing  

Once you’re in Snowflake, you can enable any number of “virtual data warehouses”, which are effectively the compute engines that power query execution. Virtual data warehouses are available in eight “T-shirt” style sizes: X-Small, Small, Medium, Large, and X- to 4X-Large. Each data warehouse size has a compute credit designation. As you go up in size, credits usage will vary. Refer to Table 1.

Table 1 – Snowflake Warehouse Sizes and Credit Usage

Based on our internal benchmarks, performance improves linearly as the size of of warehouses increases.

No charge for idle compute time

All queries run automatically from the data warehouse from which a query is launched.  What’s cool about Snowflake is that it allows you to specify a warehouse to shift into suspend mode if no queries are actively running. Once suspended, charges are also suspended for idle compute time (Figure 1).

Figure 1 – Snowflake Pricing Tracks With Actual Usage

Automatically restart the warehouse to process a new query. No manual re-provisioning required. This is more graceful than terminating a service, as required with other cloud-based solutions, to stop charges.

When you terminate services (to stop billing), with other cloud data warehouse solutions, you lose the data since it will be unloaded from the data warehouse. If you later need to run queries against that data, you will have to re-provision the data warehouse and reload the data all over again. This is disruptive and inefficient. Because of this disruption, these cloud data warehouse solutions must remain on and active, 24×7, with the meter running, whether you are running queries or not. Further, with other cloud data warehouses, if terminated services are restarted, unused credits do not roll over.

No hidden quotas or price bumps

When you run queries in Snowflake, there are no added usage quotas or hidden price premiums. You pay only for what you use.

Other cloud data warehouse solutions may not charge based on time, but rather will charge based on how many terabytes are scanned or how many terabytes are returned from a query. In addition, you may have no ability to control the compute resources available to you because you are given an allocation of processing units or slots. And if the query you run consumes more than the allocation provided to you, you are charged a premium.

True cloud-scale elasticity

On-premises data warehouses, particularly, make it nearly impossible to scale down hardware once installed and provisioned. This is cost prohibitive because most on-premises implementations are pre-sized and purchased for peak demand period, which could be for just few days a month or year, leaving massive investments idle the rest of the time.

Keeping it simple, cost-effective and price-efficient

Unlike traditional data warehouse technology (on-premises or in the cloud) never designed for the cloud, Snowflake’s cloud-built data warehouse-as-a-service makes analytics and budgeting easy. We also make it as cost-effective as possible for you to get all the insight from all your data at a fraction of the time required by your current solution. By avoiding the headaches of traditional solutions, Snowflake enables you to focus on strategic data analytics and engineering projects that advance your business.

 

The post How Usage-Based Pricing Delivers a Budget-Friendly Cloud Data Warehouse appeared first on Snowflake.

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