BQ lens FAQ
BigQuery Pricing FAQ
Have questions about BigQuery’s newly-released pricing Editions and Compressed Storage? We’ve got the answers here.
BQ lens FAQ
BigQuery Editions & Compressed Storage Questions

If you still have unanswered questions, submit your question here and we’ll update you when the answer gets added to the page!

General
1. On-demand: a ~25% price increase goes into effect July, 5th 2023
2. Flat-rate: Existing commitments will remain active until the commitment’s end date, but:
  • a. Monthly & Yearly commit: This product will be discontinued, starting July, 5th 2023
  • b. Flex slots: This product will be discontinued & transferred into BigQuery Autoscaling, starting July, 5th 2023
 

It depends on your type of workload. Customers that have a lot of idle slots while using Flat-rate might benefit from a cost reduction by switching to an Edition + Autoscaling Model. This can be combined with the new Compressed Storage Pricing, which will reduce the costs on the other side of
the equation.

Overall, the price impact should be examined from a TCO perspective.

For example, let’s assume you currently have some projects using on-demand pricing, some using flat-rate:

• On-demand costs (for workloads/projects that use it) will go up
• Your spend on commitments may go down because you can commit to a lower baseline of slots and use autoscaling for the rest
• Autoscaling may increase costs vs.
Flex slots
• Storage costs will go down if you can switch to Compressed Storage

Overall, this may still mean a customer’s BQ spend is lower than before, or the increase in spend is reduced vs. if you were just looking at one variable.

 

A BigQuery commit gives you a better price for the Slot/Hour. For example, a 3-year BigQuery commit will unlock a 40% discount on Analysis costs. Note that Storage pricing is not discounted.

You can use our BigQuery Current Usage Analysis Tool to understand the impact of each of the pricing models on your costs. Just create a duplicate Sheet and follow the instructions.

Technical
Yes, you can select different Editions for different Workloads. Basically, one project can be on using the on-demand pricing model, while another project is on the Enterprise Edition and the other one on Standard Edition.
It depends on a few factors: If you use any code to orchestrate buying of Flex slot capacity dynamically, this will no longer work after July 5th, 2023, since auto-scaling will take over. Google is actively working on support for terraform (until then you have to set an ignore_changes policy) Your SQL will run fine, no changes required. However, you might want to re-architect to reduce the amount of total slots consumed.

On July 5th all existing Flex slot reservations will be automatically migrated to auto-scaling.

Storage was always a bit “too expensive” on BigQuery and Google addressed this by making Compressed Storage Pricing available. It’s an “exclusive” feature, which means that you need to have Editions or pure-on-demand workloads. Other than that, you will always benefit from better storage pricing. However, as the compression-ratio depends on the data structure, so does the savings. Read our Compressed Storage Overview for a comprehensive overview of Compressed Storage and in which situations to enable it.

No, you cannot. Google has stated that the UI and other tooling actively checks if flat-rate reservations exist and will not allow enabling of Compressed Storage.

You will be billed for the uncompressed data volume and not the compressed. This means that there is not a cost advantage to querying compressed data with a query running from an on-demand project.

If on Editions (versus on-demand) then yes, you will be billed for the first full minute of the query.

No, the long-term storage mechanism will stay the same and still apply to both compressed and uncompressed storage.

Compute is now more expensive. And since dbt (when running on BigQuery) is compute-heavy of compute so therefore will be more expensive.

Open Monitoring in the Google Cloud Console and click on Metric Explorer in the navigation pane. From there, search for Slot metrics.

If you’re a DoiT customer you can open a ticket with a BigQuery expert to review this together.

Still have questions?

If you’re a DoiT customer you can work with a BigQuery expert on your specific use case by opening a ticket in the DoiT Console.

Not a customer? Get in touch with us about working with DoiT
on BigQuery and beyond!