DBTA 100 2026: The Companies That Matter Most in Data

The big data and analytics space has been shaken up by the increasing pressure to integrate AI into the business or be left behind. However, diving headfirst without guardrails can be a high-stakes introduction to AI. To help bring new resources and innovation to light, each year, Database Trends and Applications magazine showcases the DBTA 100, a list of forward-thinking companies seeking to expand what's possible with data for their customers. Spanning the wide range of established legacy technologies, from MultiValue to cutting-edge breakthroughs such as AI, semantic layers, data lakehouses, data mesh, and data fabric, the DBTA 100 is a list of hardware, software, and service providers working to enable their customers' data-driven future. Read More

Game-Changing Technologies Fueling The Data-Driven Enterprise In 2026

What technologies for the data-driven era are emerging now? As you might guess, much of the activity seen across the market is connected to AI. At the same time, there is a critical data element that needs both to support AI implementations, as well as be supported by AI. DBTA queried industry leaders to get their views on the most compelling technologies now emerging in this data-driven era. Read More

More Than Hype: How DBAs Can Ensure AI Adds Real Value

According to recent data from the SolarWinds "State of Monitoring and Observability Report," 51% of IT pros believe database performance would benefit from better observability. Oftentimes, database observability suffers because teams have multiple, disparate observability and monitoring tools. This tool sprawl creates blind spots that make it harder to identify and react to database performance issues. Read More

Is That Job Opening You Just Applied to Even Real?

A pattern keeps surfacing, and it's hard to ignore. In conversations with IT professionals—many currently employed, but quietly exploring new opportunities—a troubling trend has emerged. They've applied to dozens of roles for which they are clearly qualified and receive nothing in return—not even meaningful rejections, just silence. Read More

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Columnists

Database Elaborations

Todd Schraml

Language is Always Hard Words such as "taxonomy" and "ontology" are often thrown around by data architects as if these terms were interchangeable. Generically, the ideas of taxonomy and ontology are similar, but not synonymous.

DBA Corner

Craig S. Mullins

The Cost of ‘Good Enough’ SQL in a High-Volume Database Environment In many environments, there is a quiet compromise that gets made every day. It rarely shows up in project plans or architecture diagrams. No one formally approves it. But it happens, nonetheless. "Good enough" SQL gets promoted to production.

SQL Server Drill Down

Kevin Kline

More Than Hype: How DBAs Can Ensure AI Adds Real Value According to recent data from the SolarWinds "State of Monitoring and Observability Report," 51% of IT pros believe database performance would benefit from better observability. Oftentimes, database observability suffers because teams have multiple, disparate observability and monitoring tools. This tool sprawl creates blind spots that make it harder to identify and react to database performance issues.

Emerging Technologies

On Assignment: Inside Recruitment Databases—How Candidates Get Found (or Missed) As part of my On Assignment LinkedIn article series, I've continued to explore what candidates rarely see: the inner workings of recruitment databases and how recruiters actually use them in real time. This assignment took me deeper into a critical but often overlooked part of the hiring ecosystem: how resumes are categorized, stored, and retrieved and how small details can dramatically impact whether a candidate is ever seen.

Next-Gen Data Management

Will AI Become Our Friend or Foe? Technology Professionals Weigh In. Picture this: there's a new face in the IT department, ready to step in to help tackle the increasingly complex challenges caused by modern hybrid on-prem and multi-cloud environments. Overstretched technology teams always appreciate an extra set of helping hands, but what happens when this new team member isn't human—but artificial intelligence (AI)?