Google aims to use Gemini, its suite of generative AI models, to improve the functionality of your app’s databases.
During its annual Cloud Next conference in Las Vegas, Google unveiled the public preview of Gemini in databases. This collection of features aims to streamline the entire database journey, according to the company. Simply put, Gemini in Databases is a collection of tools designed for Google Cloud customers to help them with creating, monitoring, and migrating app databases. AI powers these tools, specifically for developers.
The Gemini suite includes Database Studio, a useful tool for working with structured query language (SQL). It allows for efficient data storage and processing in relational databases. Integrated within the Google Cloud console, Database Studio has the capability to identify, summarize, and resolve specific SQL code errors, as stated by Google. It also provides general SQL coding suggestions through a chatbot-like interface.
Database Studio, a part of the Gemini in Databases brand, now offers AI-assisted migrations through Google’s Database Migration Service. According to Google, the Gemini models have the ability to convert database code and provide explanations of the changes, along with recommendations.
In Google’s new Database Center, users have the ability to interact with databases using natural language and can easily manage a fleet of databases. Google gives them tools to evaluate their databases’ availability, security, and privacy compliance. If any problems arise, users can seek assistance from a Gemini-powered bot for troubleshooting tips.
According to Andi Gutmans, the General Manager of Databases at Google Cloud, Gemini in Databases allows customers to effortlessly create SQL queries. Moreover, it empowers them to efficiently oversee and enhance multiple databases from a centralized interface. Lastly, it leverages AI to expedite database migrations through code conversions. In a blog post, Eltrys received these insights from Gutmans. Imagine the ability to inquire about the status of your production databases in East Asia, such as identifying any missing backups within the last 24 hours. Or, consider being able to determine the number of PostgreSQL resources with a version greater than 11 and receive immediate insights about your entire database fleet.
That assumes, of course, that the Gemini models don’t occasionally make errors, which is not always certain.
Nevertheless, Google is moving forward by integrating Gemini into Looker, its business intelligence tool.
Introducing Gemini in Looker, a cutting-edge feature that allows users to effortlessly interact with their business data. Google has recently unveiled this exciting addition in a blog post. Incorporated into Workspace, Google’s collection of business productivity tools, Gemini in Looker covers a wide range of features, including conversational analytics, generating reports, visualizations, and formulas, as well as automating Google Slide presentations.
I’m interested in assessing the reliability of Gemini in Looker’s report and presentation generation. Generative AI models are not known for their accuracy, which can result in embarrassing or even mission-critical errors. We will have to wait and see how Cloud Next develops over the course of the week.
Microsoft’s Copilot in the Azure SQL Database may face competition from Gemini in databases. Microsoft recently introduced generative AI to their fully managed cloud database service. Microsoft is striving to maintain a competitive edge in the emerging AI-driven database competition. Additionally, the company has made significant efforts to develop generative AI using Azure Data Studio, its suite of enterprise data management and development tools.
