Google Cloud databases are being rebuilt for the age of AI agents

AI agents depend on the quality and accessibility of the data behind them, placing Google Cloud databases at the center of that equation.

The agentic data cloud introduced at Google Cloud Next 2026 underscores Google’s push to position its databases as the foundation of AI-driven enterprise architecture. Models are advancing, but without enterprise data, they lack real value, according to Sailesh Krishnamurthy (pictured), vice president of engineering for databases at Google Cloud.

“The models are amazing. The models surprise us every day, they can do a lot of work, but they don’t have all the context,” Krishnamurthy said. “The context is in the data. The heart of the data is actually stored in these systems. You need to provide that context in order to answer the questions.”

Krishnamurthy spoke with theCUBE’s John Furrier at Google Cloud Next, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Google Cloud databases are evolving from passive storage systems into intelligent context hubs that power agentic AI applications. (* Disclosure below.)

Google Cloud databases evolve into agentic context engines

The shift reshaping database architecture is not merely one of scale — it is one of purpose. For 50 years, databases had one job: store data and return exact results on demand, Krishnamurthy noted. AI breaks that contract entirely. Today’s applications need the best results, not just exact ones, demanding that graph traversal, vector embeddings, full-text search and relational operations coexist in a single system rather than forcing costly, unnecessary data movement.

“When you have this opportunity to look at data as a graph, look at data with vector embeddings, do semantic search or full-text search — all of a sudden, it’s not about getting the exact results, but getting the best results and the best quality,” Krishnamurthy said. “You don’t need to unnecessarily move the data just to organize it in a different way. I think [that’s] the big change for databases.”

Google also announced Spanner Omni, a downloadable edition of its globally distributed database that can run on-premises or across rival clouds, extending Google-scale infrastructure to wherever enterprise data lives. Agentic migration tooling powered by Gemini is also accelerating the path for organizations looking to move existing workloads, Krishnamurthy explained. Migration agents can now handle not just schema and data but the application layer — including embedded SQL queries — dramatically compressing timelines that once required months of manual effort.

“Today, what you can do with agents is you can dramatically change how fast you can migrate your systems,” he said. “It’s not just the database. When you think about database migration, you have schemas and you have data, but you have the application with complexity — the application has SQL queries embedded in it. Today, with the power of Gemini, we are excited that people are able to migrate their whole application stack so much faster.”

Here’s for the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Google Cloud Next.

(* Disclosure: TheCUBE is a paid media partner for Google Cloud Next 2026. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE