The Rise of the Agentic DBA

Developers love meritocracy. Software engineering professionals don’t judge individuals by the way they look, the way they dress and whether or not they use a purple-green hair dye rinse (spoiler alert, it’s actually considered a good thing)… and they never have. They tend to classify their counterparts and contemporaries on the basis of their skillset, their ability to show technical competency and their enthusiasm for the combined arts of coding and data science.

If there’s one chink in that argument, it’s a possible hierarchy between the developer community and the operations team. While the developers get to build, program and create, the Ops team are assigned the responsibility to underpin, maintain and manage. Some developers occasionally regard the sysadmins, database administrators and testing team as less skilled; the rise of DevOps has sought to unite these two streams, and platform engineering is also aiming to create and reinforce bonds, but fractures inevitably exist.

Agentic Administrators

Could a new wave of agentic AI services in the data management space actually help elevate the status of this essential function and, just maybe, actually help elevate the status of this role to the tier it deserves?

Lithuania-based tech writer Jastra Kranjec says we’re on the cusp. Citing the multiplicity of management consultancy reports in this space that suggest AI agents are about to really start helping us work (Capgemini’s Top Tech Trends of 2025 survey points to their use to boost efficiency and develop automation), Kranjec says that AI agents have now “evolved from experimental tools” into mainstream business solutions.

“Last year, even major enterprises like OpenAI, Google DeepMind, Microsoft and PwC began integrating them into their operations, proving them as one of the top AI trends. Moreover, this is just the beginning of AI agents’ growth, with market projections showing a surging adoption in the years ahead. Last year, the AI agent industry was valued at around $5.1 billion. This figure is projected to soar by a whopping 821%, reaching $47 billion by 2030,” wrote Kranjec.

While such massive percentage projections make for dizzying reading, perhaps we should centralize our focus on the actual jobs agentic AI can now take on. In the data management and manipulation space, that brings us back to the poor database administrator, could the AI DBA be about to become the real hero?

Disparate Data Drivers

Stewart Bond sees a role for this exact job function. In his role as VP of data intelligence and integration software at technology analyst house IDC, he projects that AI can now take on a central role in data orchestration and administration.

“The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now,” said Bond. “To unlock agentic AI’s full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes.”

Bond makes his comments in order to contextualize new services stemming from data streaming company Confluent. The organization is known for its real-time data platform built on Apache Kafka, an open source stream-processing technology. A new “snapshot queries” service in Confluent Cloud for Apache Flink will enable both real-time and historic data processing to happen concurrently. This company has promised that this will “make AI agents and analytics smarter” and it has also included IP filtering to add secure access controls.

Blended Data Brew: Real-Time and Batch

“Agentic AI is moving from hype to enterprise adoption,” said Shaun Clowes, chief product officer at Confluent. “But without high-quality data, even the most advanced systems can’t deliver real value.”

For AI data agents to make the right decisions, they need historical context about what happened in the past and insight into what’s happening right now, explains Clowes and his team. For example, for fraud detection, banks need real-time data to react in the moment and historical data to see if a transaction fits a customer’s usual patterns. Hospitals need real-time vitals alongside patient medical history to make safe, informed treatment decisions. But to use both past and present data, IT often has to use separate tools and develop manual workarounds, which can result in broken workflows.

Confluent’s latest service addresses that duality with its latest service by blending real-time and batch data “so that enterprises can trust their agentic AI to drive real change”, Clowes says.

The Rise of the Agentic DBA

Confluent didn’t necessarily build this technology to enable and create the agentic DBA, but Clowes points out, if the continued extension of the company’s platform makes this “workplace role” a reality, then it will surely serve IT stacks for the better.

“The rise of the Agentic DBA is already happening… and there are some very ‘human’ reasons behind it. Dealing with disruptions like anomalies, outages, or performance optimizations is distracting (to say the least) for DBAs and data infrastructure teams,” enthused Karthik Ranganathan, co-founder and CEO of cloud-native open source database company Yugabyte. “DBA agents are trained to respond and optimize automatically, allowing human workers to focus on more strategic business value tasks.”

Ranganathan says that agentic DBAs are capable of anything from performing query execution patterns to analyzing resource trends to mentoring cloud cluster health, which means all these tasks can now be dealt with automatically. This allows DBAs to avoid “alert fatigue” and learn from previously taken actions when their workload permits.

Industry Response

There are many technologies in this space now coming forward. If you’re lucky enough to get invited to an Oracle welcome keynote on a Sunday night at its tech events, this is the kind of technology that the company talks about volubly. With so many database functions now ripe for moving to automation such as patching, maintenance checks, upgrades and perhaps also data normalization and deduplication, it’s no surprise to hear the database giant talk about database automation.

Does IBM Make One?

Does IBM make something in this area too? Usually, is the safe answer. The company last month announced its answer to database automation challenges in the form of Db2 Intelligence Center, an AI-powered database management platform designed specifically for Db2 database administrators and IT professionals managing databases.

“We’ve spent years talking to Db2 database administrators, understanding their pain points, frustrations and the complexity of their workflows. The feedback we have captured is loud and clear: DBAs are tired of fragmented tools that don’t integrate with each other. They’re tired of the endless libraries of scripts where each DBA maintains his or her own variations and they’re tired of constantly reacting to problems and manually troubleshooting, as opposed to being proactive in their database management approach,” said Ani Joshi, senior product manager for Db2, IBM data and AI.

Db2 Intelligence Center is a unified, intelligent management console purpose-built for Db2 administrators. It combines advanced monitoring, AI-powered troubleshooting and query optimization into an integrated service that simplifies and accelerates many aspects of Db2 management.

Are Human DBAs Now Redundant?

With these (arguably) not insignificant automations now coming to the fore, some may ask whether we will have succeeded in making the role of the human database administrator redundant. The answer to that question is, obviously, of course no, don’t be silly.

What we’re seeing here are the mechanical repetitively rote tasks that a DBA has to undertake, now taken out of their workflow to some degree (in some cases totally) and so creating a new DBA role that can start to work more closely with the developer team, provide more business-centric value through increased proximity to commercial teams while also now working to innovate and create new data services.

Conclusion

The rise of agentic AI services in the data management space is set to elevate the status of database administrators and create new opportunities for them to work more closely with developers and provide business-centric value. With the ability to automate repetitive tasks, DBAs can focus on more strategic tasks and drive real change in their organizations.

FAQs

Q: What is an agentic DBA?
A: An agentic DBA is a database administrator who uses AI-powered tools to automate repetitive tasks and focus on more strategic tasks.
Q: Will agentic AI make human DBAs redundant?
A: No, agentic AI will not make human DBAs redundant. Instead, it will automate repetitive tasks and create new opportunities for DBAs to work more closely with developers and provide business-centric value.
Q: What are the benefits of agentic AI in database management?
A: The benefits of agentic AI in database management include increased efficiency, improved accuracy, and enhanced decision-making capabilities.
Q: Which companies are working on agentic AI solutions for database management?
A: Companies such as Confluent, IBM, and Oracle are working on agentic AI solutions for database management.
Q: What is the future of database administration?
A: The future of database administration is likely to involve increased use of AI-powered tools to automate repetitive tasks and create new opportunities for DBAs to work more closely with developers and provide business-centric value.