Cloud-Plattformen · 06.08.2026, 16:08 UTC
Agentic Future Ready With BigQuery: Continually Improving Price-Performance, Zero Effort
| Schweregrad | info |
|---|---|
| Kategorie | Cloud-Plattformen |
| Quelle | Google Cloud Blog ↗ |
| Veröffentlicht | 06.08.2026 UTC |
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In the modern data landscape, query performance tuning and managing system price-performance is challenging, especially as the number of agentic workloads increase. Even for experienced developers and DBAs, constantly analyzing query execution plans, tweaking schemas, and adding query hints with ever exploding volume, variety, and velocity of data is a never-ending cycle that drains business velocity. While performance tuning is a common practice, a modern data platform should do more. As data platforms evolve from systems of intelligence to systems of action, and analytics workloads shift from humans running a few queries per day to countless agents running many thousands of queries per minute, the old way of manual query tuning doesn’t work. When queries are generated by agents and applications automatically based on user actions, manual optimization becomes practically impossible. BigQuery has evolved from a data warehouse to the primary engine for the Agentic AI era. Building on a unique, truly disaggregated storage and compute architecture, serverless processing, and fine grained compute management, BigQuery continues to push the boundaries of autonomous query processing. Our North Star is an autonomous query processor powering both humans and agents for hands-free optimum price-performance regardless of query, schema, data, or workloads. Just in 2025, we delivered up to 35% better query performance and as much as 40% reduction in query processing costs (slot usage).
Figure 1. Summary of BigQuery price-performance improvements throughout …