NetApp has acquired DataPelago, a California-based AI data infrastructure company, in a move aimed at bringing accelerated data processing closer to where enterprise information is created and stored.
The company said the acquisition expands its portfolio by aligning GPU-accelerated processing with the storage layer. Financial terms were not disclosed, and NetApp did not provide a specific integration timetable for DataPelago's technology.
DataPelago is known for Nucleus, a universal data processing engine designed to operate across CPUs and GPUs and process data where it resides. NetApp said that approach can reduce the need to copy operational data into separate AI systems or external compute clusters.
The strategic rationale is tied to a growing bottleneck in enterprise AI deployment. As companies invest in models and graphics processors, the ability to prepare, govern and activate fragmented data has become a limiting factor for putting AI workloads into production.
NetApp said DataPelago will operate as a wholly owned subsidiary after the acquisition. The announcement also places the deal within a broader push by NetApp to strengthen its intelligent data infrastructure business, following partnerships with Cisco, Google Cloud, Red Hat and SK Telecom.
The acquisition gives NetApp a technology asset in one of the most contested areas of enterprise infrastructure: reducing the distance between stored data and accelerated computing. For customers, the promised value is lower data movement, faster processing and a more direct path from storage environments to AI and analytics use cases.
The company framed the transaction as part of its effort to make enterprise data AI-ready at the infrastructure layer. The next test will be how NetApp turns DataPelago's processing engine into product capabilities without overextending the claims around performance, cost reduction or deployment timing.
