Databases are often overlooked in the rush to implement AI capabilities. But valuable data that fuels AI applications — how it’s stored, organized and retrieved – comes down to a database (DB). Or thousands of databases.
As AI capabilities mature and proliferate, databases and database management are undergoing a significant transformation, bringing unprecedented complexity and new opportunities. As organizations manage thousands of databases across on-premises, cloud, and hybrid environments, the demand for fully managed and self-healing systems is rising, according to Ashish Mohindroo, general manager and senior vice president with Nutanix.
“In the database world, it's an exciting time with tremendous innovation,” said Mohindroo, who leads the team behind Nutanix Database Service technology. “AI is really pushing that envelope, but now you have to manage all kinds of databases in parallel.”
In a video interview with The Forecast, Mohindroo described the shifts occurring in the world of databases due to the rise of AI. In a 30-year career, Mohindroo began with applications and eventually transitioned to databases, where he has become a leading expert on database architectures and automation.
Throughout his career, DB developers automated a growing list of database functions. But it’s not enough these days.
“You need higher automation to deliver the quality of service that applications have become accustomed to or are demanding from these underlying systems,” Mohindroo added.
AI and machine learning tools are delivering that higher automation.
The Changing Database Terrain
Conventional relational databases store information in tightly structured formats like the columns and rows of a spreadsheet. Financial organizations and government agencies depend on the structured data in relational DBs.
With the advent of AI a new category of database has emerged: vector database.
A relational database enables computers to automate manual tasks by performing the same actions consistently. A vector database makes it easy for machine learning models to process ambiguous data and infer the degree to which things are similar or different.
A relational DB is like a U.S. history textbook’s index, pointing readers to all the appearances of George Washington or Abe Lincoln. A vector DB is like a supercharged search engine that understands the relevance of Lincoln and Washington, even if the searcher doesn’t mention their names.
For all its benefits, AI at enterprise scale ramps up the complexity of designing, implementing and managing relational, vector and other DBs in the same IT environment.
“Each database goes through a whole lifecycle from provisioning, scaling, backup and recovery, cloning, patching, upgrades and then decommissioning,” Mohindroo said. “And with every variety of database, it's done very differently.”
DB varieties mushroomed in the cloud era as developers increasingly built cloud-native architectures relying on microservices and containers.
“Large organizations typically have 100,000 to 200,000 of these databases spread across the globe, some on-premises, some in the cloud, some working in hybrid environments,” Mohindroo said. He explained that every DB has a lifecycle requiring precise configurations and prudent oversight.
Moving Databases into the Future
The database ecosystem has grown complex, almost too much for humans to handle, giving rise to managed database services that automate everyday DB chores have become pervasive. Mohindroo explained that the Nutanix Database Service (NDB) helps IT teams by handling many of the essential tasks and nuances of on-prem and hybrid cloud environments.
“NDB today supports six database engines,” he said. “You can have a relational database, you can have a NoSQL database or a document database. You can have a vector database. We don't differentiate.”
Mohindroo noted that Nutanix customers are increasingly shifting from hypervisors and virtualization to microservices and containers that require specific database functionality. He said customers are pushing for adding more AI capabilities to manage their IT platforms, including the use of prompts to provision and more AI-based automation.
Mohindroo’s Database Journey
Thirty years ago, Mohindroo started his first tech job as a software developer. Because he was a frontend dev, DBs were mostly in the background. Mohindroo soon moved into product management.
“I got a tremendous experience in terms of how products are built from the ground up,” he recalled.
He started at a small company, where he learned about a wide array of corporate functions that people never see in big organizations. Eventually, he moved to bigger companies, taking on greater executive responsibilities. By 2016, he was a vice president at Oracle, the relational database titan.
“I actually went from development to product management to marketing to general management, to back to running engineering,” he noted.
That experience laid the groundwork for his move to Nutanix in 2024. He had a front-row seat for the transition from internet to hybrid multicloud architectures that run virtual machines and containerized applications. The dot-com boom, mobile revolution, social media and now the AI transformation all happened on his watch.
“Just when you think you're settling into one architecture, a disruption takes place,” he said. “That keeps it really exciting and fresh because it constantly forces you to learn new things, but some of the core principles remain the same.”
For Mohindroo, designing high-quality software is paramount. Delighting customers is mandatory.
“You have to focus on solving a problem,” he said.
He believes customers stay loyal through waves of disruption if companies keep relieving their pain points.
“It's an exciting time because we are driving that change with our customers and, more importantly, internally across all functions of our business,” he concluded.
Editor’s note: Learn more about Nutanix Database Service capabilities in this NDB overview video on YouTube.
Tom Mangan is a contributing writer. He is a veteran B2B technology writer and editor, specializing in cloud computing and digital transformation. Contact him on his website or LinkedIn.
Ken Kaplan contributed to this story. He is Editor in Chief for The Forecast by Nutanix. Find him on X @kenekaplan and LinkedIn.
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