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Google’s Gemini comes to databases

Google wants Gemini, its family of generative AI models, to power your app’s databases — in a sense.

At its annual Cloud Next conference in Las Vegas, Google announced the public preview of Gemini in Databases, a collection of features underpinned by Gemini to — as the company pitched it — “simplify all aspects of the database journey.” In less jargony language, Gemini in Databases is a bundle of AI-powered, developer-focused tools for Google Cloud customers who are creating, monitoring and migrating app databases.

One piece of Gemini in Databases is Database Studio, an editor for structured query language (SQL), the language used to store and process data in relational databases. Built into the Google Cloud console, Database Studio can generate, summarize and fix certain errors with SQL code, Google says, in addition to offering general SQL coding suggestions through a chatbot-like interface.

Joining Database Studio under the Gemini in Databases brand umbrella is AI-assisted migrations via Google’s existing Database Migration Service. Google’s Gemini models can convert database code and deliver explanations of those changes along with recommendations, according to Google.

Elsewhere, in Google’s new Database Center — yet another Gemini in Databases component — users can interact with databases using natural language and can manage a fleet of databases with tools to assess their availability, security and privacy compliance. And should something go wrong, those users can ask a Gemini-powered bot to offer troubleshooting tips.

“Gemini in Databases enables customer to easily generate SQL; additionally, they can now manage, optimize and govern entire fleets of databases from a single pane of glass; and finally, accelerate database migrations with AI-assisted code conversions,” Andi Gutmans, GM of databases at Google Cloud, wrote in a blog post shared with TechCrunch. “Imagine being able to ask questions like ‘Which of my production databases in east Asia had missing backups in the last 24 hours?’ or ‘How many PostgreSQL resources have a version higher than 11?’ and getting instant insights about your entire database fleet.”

That assumes, of course, that the Gemini models don’t make mistakes from time to time — which is no guarantee.

Regardless, Google’s forging ahead, bringing Gemini to Looker, its business intelligence tool, as well.

Launching in private preview, Gemini in Looker lets users “chat with their business data,” as Google describes it in a blog post. Integrated with Workspace, Google’s suite of enterprise productivity tools, Gemini in Looker spans features such as conversational analytics; report, visualization and formula generation; and automated Google Slide presentation generation. 

I’m curious to see if Gemini in Looker’s report and presentation generation work reliably well. Generative AI models don’t exactly have a reputation for accuracy, after all, which could lead to embarrassing, or even mission-critical, mistakes. We’ll find out as Cloud Next continues into the week with any luck.

Gemini in Databases could be perceived as a response of sorts to top rival Microsoft’s recently launched Copilot in Azure SQL Database, which brought generative AI to Microsoft’s existing fully managed cloud database service. Microsoft is looking to stay a step ahead in the budding AI-driven database race and has also worked to build generative AI with Azure Data Studio, the company’s set of enterprise data management and development tools.

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