Snowflake pushes interoperability-first vision as Apache Iceberg gains enterprise momentum
As AI adoption accelerates, open data architectures are becoming essential to help organizations access and share data across platforms. Apache Iceberg interoperability and other open standards are increasingly viewed as the key to reducing complexity and unlocking greater value from enterprise data.
Interoperability without compromise reflects a vision of creating an open, connected data ecosystem that extends from the underlying data foundation to how information and products are shared across and within organizations. At the core of that approach is Apache Iceberg, according to James (JRJ) Rowland-Jones (pictured, left), director of product management at Snowflake Inc.
“As you come up through that stack, what you’re trying to achieve is an ecosystem where any engine can both read and write to that data, whether that’s a human or an agent being able to get direct access to that data,” Rowland-Jones said. “In this AI-powered era, that’s what’s so important, is being able to open that ecosystem up as much as humanly possible.”
Rowland-Jones and Russell Spitzer (right), principal engineer at Snowflake Inc., spoke with theCUBE’s Dave Vellante and Rebecca Knight at Snowflake Summit 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the rise of open, interoperable data architectures and the growing importance of Apache Iceberg interoperability in enabling seamless data access, governance and sharing across the AI ecosystem. (* Disclosure below.)
