Google's Gemini Database Solution Arrives

Google Wants Gemini, its Family of Generative AI Models, to Power Your App’s Databases

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 simpler terms, Gemini in Databases is a bundle of AI-powered, developer-focused tools for Google Cloud customers who are creating, monitoring and migrating app databases.

What is Gemini?

Gemini is a family of generative AI models developed by Google. These models have been designed to power various applications, including databases. In the context of databases, Gemini is being used to create a suite of developer-focused tools that can simplify database management.

Gemini in Databases: A Collection of Features Underpinned by Gemini

The public preview of Gemini in Databases is a significant development for Google Cloud customers who are creating, monitoring and migrating app databases. The collection of features underpinned by Gemini includes:

Database Studio: An editor for structured query language (SQL), the language used to store and process data in relational databases. Database Studio can generate, summarize and fix certain errors with SQL code, Google says.
AI-assisted migrations: Via Google’s existing Database Migration Service, users can convert database code and deliver explanations of those changes along with recommendations.
Database Center: A component where users can interact with databases using natural language and manage a fleet of databases with tools to assess their availability, security and privacy compliance.

Gemini in Databases: Enabling Easy SQL Generation, Database Management and Migration

According to Andi Gutmans, GM of databases at Google Cloud, Gemini in Databases enables customers to easily generate SQL, manage, optimize and govern entire fleets of databases from a single pane of glass, and accelerate database migrations with AI-assisted code conversions.

Gemini in Looker: A Private Preview of Conversational Analytics

In addition to Gemini in Databases, Google is also launching Gemini in Looker, its business intelligence tool. The private preview of 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: Users can interact with their business data using natural language.
Report and presentation generation: The tool can generate reports and presentations based on user input.

Gemini in Databases: A Response to Microsoft’s Copilot

The launch of 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 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.

Conclusion

The public preview of Gemini in Databases marks a significant step forward for Google Cloud customers who are creating, monitoring and migrating app databases. With its collection of features underpinned by Gemini, users can easily generate SQL, manage, optimize and govern entire fleets of databases from a single pane of glass, and accelerate database migrations with AI-assisted code conversions.

Related Topics

AI: The technology used to develop the Gemini family of generative AI models.
Generative AI: A type of artificial intelligence that can generate new content based on user input.
Databases: The collection of data and associated management systems that allow users to store, manage and retrieve data.
Microsoft Copilot: A tool developed by Microsoft that brings generative AI to its existing fully managed cloud database service.

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