Imagine a world without reliable databases. Banking systems would grind to a halt. E-commerce would collapse. The AI revolution driving today's innovation wouldn't exist. Yet as organizations embrace AI and cloud technologies, the very foundation of data management is undergoing a fundamental transformation.
In a recent video interview with The Forecast, Ashish Mohindroo, senior vice president and general manager for Nutanix Database Services (NDB), explored how database management is evolving to meet the demands of modern enterprises. He explains why it's becoming exponentially more complex.
"At the heart of AI is data," Mohindroo explained. "You have to train the model, which requires massive quantities of data, and then you have to retrieve information, which is also dependent on data."
The challenge? Ensuring databases function reliably and securely at a scale most organizations have never encountered before.
From CRM to Database Innovation
Mohindroo's career trajectory mirrors the evolution of enterprise technology itself. Starting with CRM and e-commerce applications before focusing on database innovation, including nearly a decade at Oracle, he's witnessed what he calls several "tectonic shifts" in IT over the past 30 years: the rise of client-server technology, the internet boom, cloud services, mobile computing, and now artificial intelligence.
Today, he oversees Nutanix’s database technology business, including engineering, market strategy, and financial performance. The company's approach, he says, centers on flexibility: Nutanix Database Services (NDB) is a multi-database platform that allows organizations to "do everything you would expect from a fully managed database service, but within the confines of their own data centers or even across hybrid clouds."
A recent video showcases this in action, demonstrating how IT teams at Westgate Resorts leverage Nutanix Database Services to power their business-critical applications.
The Developer-Driven Database Explosion
The AI revolution isn't just changing how organizations use data, it's fundamentally altering how they leverage a variety of database architectures. Mohindroo notes that developers increasingly favor specialized databases that integrate seamlessly with microservices and cloud-native designs.
"There's a lot more choice given to developers, and they can pick best-of-breed or best-in-class databases to construct their applications," he said.
But this freedom comes at a cost. Organizations now manage thousands, sometimes hundreds of thousands of databases across on-premises, cloud, and hybrid environments. The scale is staggering.
"Large organizations typically have 100,000 to 200,000 databases spread across the globe," Mohindroo revealed. "The complexity rises exponentially as you increase the variety of databases. You're not just talking about 10 or 20 databases anymore."
This explosion in database diversity has created demand for fully managed database services that can handle lifecycle management, updates, and security across multiple database types simultaneously.
Navigating the Shift to Containers
Adding another layer of complexity, the industry is transitioning from traditional virtualized environments to containerized architectures. Mohindroo says Nutanix is adapting its platform accordingly.
"We're moving in that direction, supporting databases running on hypervisors and soon adding support for managing databases on containers as well," he explained.
Meanwhile, rising awareness of AI capabilities is pushing customers to demand more intelligent automation.
"They're really looking for us to add more AI capabilities into our platforms," Mohindroo said, citing examples like provisioning and managing databases through natural language prompts and embedding AI-based automation throughout the platform.
Constant Disruption, Constant Innovation
For Mohindroo, the relentless pace of change is both challenging and exhilarating.
"It's an amazing time because of the tremendous innovation, and AI is really pushing that envelope," he reflected.
"Complexity has gone up dramatically. Just when you think you're settling into one architecture, a disruption takes place in our industry. That keeps it exciting and fresh because it constantly forces you to learn new things."
As databases evolve from simple data repositories to the critical infrastructure powering AI and cloud-native applications, organizations face a choice: adapt to manage unprecedented complexity, or risk falling behind in an industry where standing still is impossible.
Transcript:
Ashish Mohindroo: Now is an amazing time because with AI, it's an incredible transformation that's taking place, and it's changing everything. The way we write technology or software, the way we consume it now, is completely different.
Jason Lopez: In today's AI-driven era, database developers face unprecedented complexity in managing the growing scale. Speed and diversity of data
Ashish Mohindroo: Databases have to be available at a very high percentage of the time.
Jason Lopez: Thousands of databases across on-prem, cloud, and hybrid environments have become too complex to maintain manually. It drives demand for fully managed and self-healing systems. As Nutanix executive Ashish Mahindra explains, this convergence of AI automation and data diversity is transforming database development into one of the most challenging and innovative frontiers in modern computing.
Ashish Mohindroo: So the complexity really rises as you increase the variety of databases. Plus, if you're running them at scale, you're not just talking about 10, 20 databases. 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. So you can imagine it's not easy to manage them. You can have structured data, which is typically stored in relational databases. You have unstructured data, which is stored in document databases, and now, more so you have, because of AI, what we call vector databases. So this is a new category of databases that has emerged. So in the database world, it's an exciting time. There's tremendous innovation, and AI is really pushing that envelope. But now you have to manage all these kinds of databases and parallel. So that complexity has really gone up, and you need higher automation to really deliver the kind of quality of service the applications have become accustomed to or are demanding from these underlying systems. There's more specialization taking place. So I want a persistent store. So that may be your SQL database or a relational database. You want a document store. So then you have A-J-S-O-N base structure in there, and now you may have vector databases. So there's a lot more choice given to developers, and they can pick best of breed or best in class databases to construct their application. What is really important is to deliver that data into an AI system so that can consume it, process it, and then display it or send the information to the user in a timely fashion. That means these databases have to be available at a very high percentage of the time. You can't have the system go down because if that goes down, then your AI system gets impacted by it. So you really need high availability. You also need high security, so you want to make sure the information is secured, it's not being tampered with. So that also needs to be brought into that stuff. And there's a concept of business continuity, which is related to high availability. So, if something does happen to your data, which gets corrupted, or is the data center disruption, that you still have the ability to do disaster recovery fail over in a timely manner? So databases have become even more important in that context of delivering high-quality data to any one of these systems of the AI or something else.
This is where NDB or Nutanix Database Services platform really excels. We drive that automation to deliver to our customers the same experience as a fully managed database service, but within their own controls, security policies, and personnel. So, this is a very powerful offering because they can now do everything that you would expect from a fully managed database service, but within the confines of their own data centers or even across hybrid clouds. And we do that by delivering them tremendous value because what would take an army of developers and database operators or cloud experts, cloud ops teams, I would say, to deliver that fully managed service, we are able to do that with very few resources within those organizations. So that's the whole promise, or I would say the whole value proposition ofNDB and why our customers are gravitating towards it. When you talk about A-W-S-R-D-S, they're focused on relational databases. When they're talking about Aurora or Dynamo or db, they're definitely focused on one specific kind of database. With NDB, what we really offer our customers is flexibility and choice of database. So we support any kind of database. You can have a relational database, you can have a NoSQL database or a document database. You can have a Vector database. So we don't differentiate. We offer the same capabilities across any one of these environments or any other database engines, I should say.
Today, we do a very good job of supporting databases or managing databases running on hypervisors, and then we'll be very soon adding support for them, managing those databases on containers as well. The third area that they're really looking for is adding more AI capabilities into our platform. So, how do you really ingest a lot of these AI capabilities? So you can do prompt-based management of the databases, so you can provision them using prompts, you can actually manage them using prompts, and also deliver more AI-based automation into the platform. So all of these things are something that we are adding onto NDB, and we have a roadmap to deliver that in a timely basis. I started my career in what we call CRM or customer relationship management applications and e-commerce. So you never really thought about the database. The database was always there in the backend. So I started as a developer, and then I'm product manager and then a business manager. And you never really felt like, Hey, I need to worry about the database. It was more about application and application logic. It just so happened my career transitioned. So I went from applications to a middleware company to a database company, and now Oracle. So it was basically startups to a company called BEA Systems, which is a leader in middleware and application servers. That's where all the application logic is written, business logic is written, and then that layer interacts with the database. And I ended up working for Oracle, which is a database company, the premier database company. So I kind of fell into it, and then the process and the journey, I learned about the importance of the databases. And it's interesting when, typically there are two paths. Either you start at the lower end of the application stack and go up. I ended up starting at the top end of the application stack and going down, and I continuously kind of marveled at how much work the database layer actually performed to make life easier for the other layers of the stack. And I just fell in love with it. I just fell in love with how critical it is to have the right databases, the technology and everything it does behind it to make our lives easier.
Ken Kaplan is Editor in Chief for The Forecast by Nutanix. Find him on X @kenekaplan and LinkedIn.
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