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Infra & Chips · Google Cloud AI Blog

QueryData helps agents turn natural language into queries for AlloyDB, Cloud SQL and Spanner

QueryData launches in preview today.

Apr 10, 2026 16:00 UTC · ~5 min read · Research
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  • May affect how AI can be used.
  • It is a tool for translating natural language into database queries with near-100% accuracy.
  • With QueryData, you can build agentic experiences across AlloyDB, Cloud SQL (for MySQL and PostgreSQL), and Spanner (for GoogleSQL).

Context

It is a tool for translating natural language into database queries with near-100% accuracy. With QueryData, you can build agentic experiences across AlloyDB, Cloud SQL (for MySQL and PostgreSQL), and Spanner (for GoogleSQL). It builds upon Google Cloud’s #1 spot in the BiRD benchmark , one of the world's most competitive benchmarks for natural-language-to-SQL – as well as upon Gemini-assisted context engineering. Developers are already seeing the benefits from QueryData, including Hughes Network Systems, a leader in telecommunications, that deployed QueryData in production. “Google Cloud AI Blog has transformed user support operations with Google Cloud’s data agents. At the heart of Google Cloud AI Blog's solution is QueryData, enabling near-100% accuracy in production. Google Cloud AI Blog is excited about the future of agentic systems!" - Amarender Singh Sardar, Director of AI, Hughes Network Systems The opportunity for agentic systems: from intent to action Agentic systems are evolving from human-advisory roles into active decision-makers. To execute business actions accurately, agents require precise information from operational databases (such as pricing, inventory, or…

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It is a tool for translating natural language into database queries with near-100% accuracy.

It is a tool for translating natural language into database queries with near-100% accuracy.

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