Denodo named Gartner leader for seventh year in row

Denodo has been named a Leader in Gartner's 2026 Magic Quadrant for Data Integration Tools, marking the seventh consecutive year it has appeared in the Leaders category.

Gartner described data integration tools as a core part of data architecture for operational, analytical and AI use cases. Its research assessed 19 vendors.

The recognition comes as software suppliers and their customers place greater emphasis on automation in data management, particularly as businesses look for ways to support AI projects with governed access to data. In the report, Gartner said that by 2028, 60% of data integration tasks will be completed autonomously, freeing up 20% of data engineers' time.

Denodo linked its position to recent platform updates aimed at supporting what it describes as agentic AI. It updated the Denodo Platform twice this year, first with version 9.4 and then with version 9.5.

Those releases focused on giving AI systems, applications and users access to live data alongside business context and governance controls. The later release added what Denodo calls active context, intended to help AI systems operate within defined rules and with greater awareness of data meaning and usage conditions.

Platform updates

Denodo said the changes reflect a broader shift in customer demand, with data integration increasingly shaped by the needs of AI workloads rather than only conventional analytics or operational reporting. That puts more scrutiny on how vendors manage data access, lineage, governance, and the mix of structured and unstructured sources.

Ravi Shankar, Senior Vice President and Chief Marketing Officer at Denodo, said the company sees data integration goals changing as AI use expands.

"The goals of data integration are now driven by the needs of agentic AI, which is for AI-ready data that is immediately integrated, governed, and supported by active context. The Denodo Platform, by establishing the critical AI data layer, provides the most flexible, direct foundation for trustworthy, AI-ready data, in support of advanced automation," said Ravi Shankar, Senior Vice President and Chief Marketing Officer at Denodo.

He added that the latest Gartner ranking reinforced the company's view of the market.

"We are extremely proud that Gartner has once again recognized Denodo as a Leader in the Magic Quadrant for Data Integration Tools, as Gartner has done for the previous six years. I feel this strengthens our conviction that an overarching, cross-platform AI data layer, with active context, provides the most effective foundation for tackling complex challenges with autonomous AI," Shankar said.

Customer ratings

Alongside the Magic Quadrant result, Denodo pointed to customer feedback on Gartner Peer Insights. The Denodo Platform has an average rating of 4.6 out of 5 from 337 ratings.

Denodo included comments from users in insurance and manufacturing who cited faster development, easier API creation, data governance features, and support for combining multiple data sources. One reviewer said semantic layer features had improved delivery times and developer productivity, while another highlighted security controls, lineage visibility, and monitoring tools.

These customer references show how data integration tools are judged in day-to-day use. Buyers are often looking beyond simple data movement, with more emphasis on governance, security, self-service access, and the ability to expose data in forms other applications and teams can use.

Denodo has built its position around data virtualization and a broader data layer approach, rather than relying only on traditional extract, transform and load methods. That model has appealed to organizations trying to work across cloud platforms, internal systems, and newer AI-driven applications without duplicating large amounts of data.

The latest Gartner ranking suggests demand for those approaches remains strong as enterprises reassess how they organize data for AI use. Gartner said data integration tools continue to serve as a foundational component for operational, analytical, and AI workloads across the market.