Google Cloud’s BigQuery, a fully managed and serverless cloud data warehouse solution, is implementing changes to its “on-demand” query pricing. These adjustments aim to help users manage costs more effectively and achieve greater spending predictability by modifying how usage is measured and charged.
These changes will take effect on September 1, 2025. Here’s what you need to know and how you can prepare.
Previously, certain BigQuery quotas, specifically QueryUsagePerDay (daily query usage per project) and QueryUsagePerUserPerDay (daily query usage per user within a project), applied broadly. Moving forward, these quotas will exclusively apply to on-demand query usage. This distinction is crucial because BigQuery offers different pricing models for query execution:
- On-Demand Pricing: You pay for the amount of data processed by your queries. This is the default and most flexible option.
- Flat-Rate Pricing (via Reservations): You purchase dedicated BigQuery processing capacity (slots) for a fixed monthly or annual fee, regardless of the data scanned.
The upcoming change means that if you are using flat-rate pricing through BigQuery Reservations, your query usage will not be constrained by these daily quotas. This provides greater consistency for dedicated workloads.
Key Specifics of the Change:
- New Projects: All newly created Google Cloud projects will have a default QueryUsagePerDay limit of 200 TiB. This ensures a baseline control on cost for new users.
- Existing “Unlimited” Projects: If your existing projects have previously been considered “unlimited” in terms of on-demand query usage, these projects will now be updated to have a custom QueryUsagePerDay limit. This limit will be intelligently derived based on your historical peak usage over the last 30 days. This approach aims to minimize disruption by aligning the new limit with your established usage patterns.
Potential Impact on Your BigQuery Workloads
The primary impact of these changes revolves around potential query failures or slowdowns if your on-demand query usage exceeds the newly applied daily quotas.
- For Projects with High On-Demand Spikes: If your projects frequently experience large, unpredictable spikes in on-demand query usage that historically went unchecked, these spikes might now hit the new daily limits, leading to query errors or throttling.
- For Projects Transitioning from “Unlimited”: While the custom limit for existing “unlimited” projects will be based on historical usage, any future usage patterns that significantly exceed this historical peak could trigger quota limitations.
- For Users Relying on Free Tier/Trial: While 200 TiB is a substantial amount for many users, those operating near or above this threshold on new projects will need to monitor their usage closely.
It’s important to reiterate that these changes are about managing on-demand query costs and resource consumption, not about increasing prices for the same amount of usage. The goal is to give BigQuery customers more control and predictability over your queries.
How to Prepare: Actionable Steps for a Smooth Transition
To ensure your BigQuery workloads continue to run smoothly and predictably after September 1, 2025, we strongly recommend the following preparatory steps:
- Understand Your Current On-Demand BigQuery Usage:
- Monitor your QueryUsagePerDay: Utilize Google Cloud’s monitoring tools (Cloud Monitoring, BigQuery Admin Resource Charts, or BigQuery logs) to understand your average and peak daily on-demand query usage (in TiB).
- Analyze User-Specific Usage: If applicable, also review QueryUsagePerUserPerDay to identify any individual users or applications that consume a disproportionately large amount of on-demand query capacity.
- Review and Adjust Project Quotas:
- For All Projects: Access the BigQuery Quotas page in the Google Cloud Console (under IAM & Admin > Quotas). Here you can view your current QueryUsagePerDay and QueryUsagePerUserPerDay limits.
- Request Higher Limits (If Needed): If your historical peak usage, or anticipated future usage, consistently exceeds the new default or auto-assigned custom limits, you can proactively request a quota increase through the Google Cloud Console. This is a standard process and allows you to set limits that align with your business needs.
- Consider BigQuery Reservations (Flat-Rate Pricing) for Predictable Workloads:
- If you have consistent, high-volume BigQuery workloads, migrating them to a BigQuery Reservation (flat-rate pricing) model is an excellent strategy. Queries run within a reservation do not consume on-demand quota and offer a fixed cost for your processing capacity. This provides ultimate cost predictability and eliminates concerns about on-demand query limits.
- Evaluate your cost-efficiency: For substantial BigQuery usage, flat-rate pricing can often be more cost-effective than on-demand pricing, in addition to providing dedicated capacity.
- Optimize Your Queries:
- Regardless of pricing model, regularly optimizing your BigQuery queries is always a best practice. Efficient queries scan less data, leading to lower costs (on-demand) and faster execution times (both on-demand and flat-rate).
- Use DRY RUN to estimate query costs before execution.
- Leverage partitioning and clustering for your tables.
- Select only the columns you need.
Timeline and Resources
These changes will go into effect on September 1, 2025. We encourage you to begin reviewing your BigQuery usage patterns and making any necessary adjustments well in advance of this date.
For detailed documentation and step-by-step guides on managing BigQuery quotas and setting up reservations, please refer to the official Google Cloud documentation:
- Working with BigQuery Quotas and Limits
- Introduction to BigQuery Reservations
- BigQuery Pricing Overview
Should you have any questions or require assistance in preparing for these changes, please do not hesitate to contact Google Cloud Support. We are here to help you navigate these updates and ensure your BigQuery environment continues to meet your analytical needs.