The data flowing through an IT system has never been more valuable to today's modern business or organization. The characteristics of that data — how clean it is, its accessibility, and its security — now have direct ties to major business initiatives, such as artificial intelligence (AI) implementation. As a result, the steward of each organization's databases, namely the database administrator (DBA), now plays a more important role than ever.
Despite their growing importance, SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points. As organizations lean more on these database managers, it's imperative to mitigate some of the issues DBAs are facing.
The Expanding Universe of the Modern DBA
Before diving into solutions for today's DBAs, it's crucial to understand how much their role has evolved and how complex it has become. While the majority still manage Oracle and SQL servers (81% according to the study), DBAs are increasingly tasked with a sprawling mix of systems and functions, from in-memory and time-series databases to NoSQL, vector databases, orchestration platforms, data lakes, and analytics tools. On top of this, these responsibilities often stretch across multiple deployment environments — on-premises, public cloud, and private cloud — creating a tangled web of integration, visibility, and maintenance challenges.
Beyond this complexity, DBAs are trapped in a relentless cycle of firefighting that consumes most of their workweek. Reactive maintenance, constant alerts, and urgent issues dominate their time, with database managers spending an average of 27 out of 40 hours handling these crises. When over half their week is spent reacting, DBAs are left with little bandwidth for the forward-looking, strategic initiatives — such as capacity planning, database optimization, or experimenting with new tools and technologies — that could unlock real business growth.
DBAs and the AI Paradox
When it comes to AI, DBAs present something of a paradox. The technology is delivering real benefits: 62% of respondents report that AI helps them diagnose performance issues faster, and 60% say it ensures more reliable and consistent execution of routine tasks. However, AI is introducing new challenges into their workflows. DBAs face oversight gaps, misaligned AI processes, and difficulties stemming from poor-quality data.
The misalignment doesn't stop there. Executives often see AI's impact differently than DBAs. For instance, 43% of DBAs flagged AI-related security and compliance challenges, compared with only 31% of IT executives. Similarly, while 50% of DBAs say oversight and manual review are critical for AI success, only 43% of IT leaders agree. When executives and DBAs aren't aligned on how and where AI is implemented, frustration grows — and the promised return on investment (ROI) of AI tools can fall short.
Creating the Right Support System for DBAs
IT execs can begin to limit DBA frustration with three steps. First, they should tap into unified observability tooling that can remove some of the monitoring complexities DBAs face. An advanced observability platform will allow DBAs to view their servers and workflows through a single pane of glass, regardless of where they are deployed, creating a unified monitoring experience. This unified visibility will help reduce alert fatigue, streamline incident diagnosis, and mitigate some of the persistent firefighting that plagues DBAs daily.
Once firefighting is limited, IT execs and DBAs should partner on what strategic work could look like for the DBA. Think outside the box about cross-functional collaboration, architectural planning, and the testing of new technologies. This will allow the DBA to participate in rewarding work that breaks through the confines of daily tasks and contributes to business growth. Finally, it's important for DBAs and IT execs to align on a plan for AI. Allocate time and budget for hands-on training and tie each AI tool deployment to a specific task with the proper oversight. This will optimize AI's role in database management while maximizing ROI from AI spend.
When organizations empower today's DBAs with the right support system — in both tooling and teamwork — they set the stage for database management that leads directly to more business success.
