NetApp Acquires DataPelago, Making Data AI-Ready at the Infrastructure Layer

NetApp, an intelligent data infrastructure company, announced it has acquired DataPelago, a California-based AI data infrastructure company recognized for its innovative approach to eliminating data processing bottlenecks for AI and analytics workloads.The acquisition marks a foundational expansion of NetApp’s portfolio, enabling GPU-accelerated data processing aligned directly with the storage layer. With this acquisition, NetApp establishes itself as the company that makes zero-copy activation of enterprise data for AI real.

AI is the defining platform shift of our era, but enterprises are discovering that their greatest bottleneck is preparing, governing, and activating their data fast enough to put AI into production. The key to accomplishing this objective is to enable accelerated computing where the data is created and stored. DataPelago solves this challenge by fundamentally reimagining where accelerated compute happens: at the data layer, not above it.

“As AI models and the chips that power them get ever more effective, enterprises need data infrastructure that is just as intelligent and powerful to harness the potential of their data,” said George Kurian, CEO, NetApp. “NetApp is leading the industry in helping customers drive innovation and generate business value by giving them full command of their most important asset: their data. With DataPelago, we are extending our ability to help customers understand and process their data with the agility required to unleash competitive advantage.”

DataPelago’s core technology, Nucleus, is a universal data processing engine that uses heterogeneous accelerated computing across CPUs and GPUs to process data where it lives. By processing data at the storage layer rather than moving it to external compute clusters, Nucleus reduces infrastructure costs by up to 80% and delivers performance up to 10 times faster than conventional approaches. In addition, by not requiring customers to copy their data from their operational systems to AI-systems, DataPelago eliminates the single biggest bottleneck in enterprise AI deployment. DataPelago’s technology is delivering value at large enterprises across multiple industries, accelerating demanding workloads while improving infrastructure efficiency at scale.

“DataPelago is on a mission to eliminate the data processing bottlenecks that prevent AI innovation from reaching its full potential,” said Rajan Goyal, founder and CEO, DataPelago. “Joining NetApp gives us the opportunity to combine our breakthrough processing technology with the industry’s best data infrastructure portfolio. Enterprises have invested billions in GPUs and AI models, but their data remains fragmented, leaving valuable computing resources to sit idle rather than putting these investments to work. Together, we’re positioned to help customers simplify and accelerate AI deployment at scale.”

“DataPelago’s Nucleus engine brings software-defined acceleration directly to the storage layer, processing data across CPUs and GPUs so enterprises can prepare, govern, and activate their data for AI without moving it. This is true zero-copy activation,” said Syam Nair, CPO, NetApp. “NetApp manages more enterprise data across more environments than anyone in the industry. The next phase of AI will be won by those who make that data work at the source, and the DataPelago team brings the technical depth and velocity to get us there faster.”

Following the acquisition, DataPelago will operate as a wholly-owned subsidiary of NetApp. This news signals a continued growth trajectory for NetApp, following recent industry-leading partnerships with Cisco, Google Cloud, Red Hat, and SK Telecom, among others.

Comments

The battle over data discovery, cataloging, sharing, and access is intensifying between infrastructure vendors operating from the storage layer upward and application-centric platforms approaching the challenge from the top down. While most players have announced strategic partnerships, they are also advancing their own technologies to protect and strengthen their market positions. Databricks' recent OpenSharing announcement is a notable example, highlighting the company's rapidly growing influence and expanding role in the AI data ecosystem.

For NetApp, a long-time leader in file-based data sharing across on-premises, cloud, and hybrid environments, the DataPelago acquisition represents a strategic move to secure a central position in this evolving landscape. It reinforces the company's ambition to enrich its Data Fabric vision with more intelligent data services while reducing operational complexity for customers.

This convergence from both the infrastructure and application sides underscores a fundamental reality of the AI era: data has become the most valuable enterprise asset.

The acquisition also validates the growing consensus that data should be processed where it resides, eliminating costly and time-consuming data movement whenever possible. Whether data lives in a traditional data center, at the edge, or in the cloud, bringing compute to the data is increasingly the preferred architectural approach promoted by vendors and embraced by customers alike.

The ability to discover, catalog, govern, normalize, unify, and provide secure access to enterprise data, potentially across organizational boundaries, has become one of the industry's hottest strategic battlegrounds. The coming months promise to be particularly interesting, as this acquisition could trigger additional consolidation across the market. Interestingly, during our recent discussion with George Kurian, CEO, NetApp, and Syam Nair, CPO, at the RAISE Summit in Paris, we anticipated that NetApp was likely to make such a move. And a few days later, boom.

DataPelago's Nucleus engine appears to be an excellent strategic fit, naturally extending NetApp's Data Fabric vision, even if the entity will operate as a wholly owned subsidiary, and strengthening its position in the race to build the next generation of intelligent data infrastructure.