Google Cloud’s BigQuery release notes list several changes from the first week of November 2026. Two of them matter for anyone learning data analytics: graph queries are now available on on-demand pricing, and cross-cloud caching for Lakehouse has reached general availability.
Confirmed facts (official source)
- 6 November 2026: You can now use BigQuery Graph and run Graph Query Language (GQL) queries when you use on-demand pricing.
- 2 November 2026: Lakehouse caching for cross-cloud data access is generally available. Cross-cloud caching is disabled by default, and you opt in to cache remote files in your Google Cloud region.
- 2 November 2026: The stated purpose of this caching is to reduce cross-cloud egress costs and speed up later queries.
- 2 November 2026: Lakehouse supports remote catalog providers for cross-cloud data access, including Databricks Unity Catalog, AWS Glue Data Catalog, Snowflake Horizon Catalog and Workday Data Lake. The release notes list this feature as generally available.
- 6 November 2026: A custom organization policy can now allow or deny specific operations on BigQuery models. This feature is in preview.
Source: BigQuery release notes, Google Cloud Documentation
Our view
Graph queries suit questions about relationships: customers linked through shared purchases, suppliers connected to delayed orders, or referral chains. Many analysts only learn SQL joins, so GQL is a useful addition to a portfolio. Because graph queries now run on on-demand pricing, a learner can try them without a reserved-capacity commitment. Costs still depend on the data each query scans, so check the pricing page before running large tests.
Cross-cloud caching is a reminder that cost is a design decision. Caching is off by default. An analyst who queries data stored in another cloud from BigQuery should know whether caching is switched on and what it will cost before enabling it.
A practical exercise: write one small graph query on sample data, then write the same question in standard SQL and compare the two. Being able to explain why you chose one approach over the other is the kind of judgement interviewers look for.
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