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Google wantsGemini , its family of generative AI exemplar , to power your app ’s database — in a sense .
At its one-year Cloud Next conference in Las Vegas , Google announced the public prevue of Gemini in Databases , a collection of features corroborate by Gemini to — as the company pitched it — “ simplify all aspect of the database journeying . ” In less jargony lyric , Gemini in Databases is a bundle of AI - powered , developer - focused tools for Google Cloud customers who are creating , monitoring and migrate app databases .
One piece of Gemini in Databases is Database Studio , an editor for integrated query language ( SQL ) , the language used to salt away and process data inrelational databases . Built into the Google Cloud console table , Database Studio can sire , sum and fix sure erroneousness with SQL code , Google says , in accession to offer general SQL inscribe suggestions through a chatbot - like user interface .
link Database Studio under the Gemini in Databases trade name umbrella is AI - help migration via Google ’s exist Database Migration Service . Google ’s Gemini models can convert database code and give birth explanations of those changes along with recommendation , accord to Google .
Elsewhere , in Google ’s new Database Center — yet another Gemini in Databases component — user can interact with database using natural language and can manage a fleet of databases with tools to assess their availability , security and privacy compliance . And should something go faulty , those exploiter can require a Gemini - powered bot to extend troubleshooting tips .
“ Gemini in Databases enables client to well generate SQL ; to boot , they can now manage , optimize and regularize full fleet of databases from a single paneling of glass ; and finally , speed database migration with AI - assist code conversions,”Andi Gutmans , GM of database at Google Cloud , wrote in a blog office shared with TechCrunch . “ reckon being able to ask questions like ‘ Which of my production database in east Asia had missing backup in the last 24 60 minutes ? ’ or ‘ How many PostgreSQL resource have a version higher than 11 ? ’ and getting instant insights about your integral database fleet . ”
That assumes , of course , that the Gemini model do n’t make mistakes from prison term to clip — which is no warranty .
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Regardless , Google ’s shape ahead , bringing Gemini to Looker , its business intelligence peter , as well .
Launching in individual preview , Gemini in Looker lets user “ chat with their business data , ” as Google describes it in a web log post . Integrated with Workspace , Google ’s suite of enterprisingness productiveness tools , Gemini in Looker bridge features such asconversational analytics ; report , visualization and formula generation ; and automated Google Slide display generation .
I ’m curious to see if Gemini in Looker ’s report and presentation generation work on reliably well . Generative AI models do n’t exactly have areputation for truth , after all , which could lead to embarrassing , or even mission - decisive , mistakes . We ’ll find out as Cloud Next proceed 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 work procreative AI to Microsoft ’s exist in full managed cloud database avail . Microsoft is looking to stay a step ahead in the budding AI - driven database race and has also worked to build up generative AI with Azure Data Studio , the company ’s set of endeavour data management and exploitation tools .
