NetApp has acquired AI infrastructure startup DataPelago to add GPU-accelerated and CPU-accelerated data processing to its storage portfolio, a move one top NetApp channel partner said could help customers’ human and machine users more easily find and use data for AI workloads.
Data storage and cloud management technology developer NetApp unveiled the acquisition of AI infrastructure company DataPelago.
Mountain View, Calif.-based DataPelago, which exited stealth mode in October 2024, is the developer of a universal data processing engine built for accelerated computing. The company said its technology is purpose-built to process any type of data, operate across any hardware and support any query engine as a way to deliver price/performance benefits that make it viable to extract value from any data.
NetApp did not disclose how much it paid for DataPelago. However, DataPelago previously said the company was launched with $47 million in funding from Eclipse, Taiwania Capital, Qualcomm Ventures, Alter Venture Partners, Nautilus Venture Partners, and Silicon Valley Bank, a division of First Citizens Bank.
[Related: NetApp CEO George Kurian On AI, Cloud Growth, Memory Shortages And What’s Next]
NetApp declined to provide information on the acquisition beyond the company’s press release. In response to an emailed request for more information, NetApp told CRN that more information would be forthcoming.
NetApp is expected to report its fiscal first quarter 2027 financials on Sept. 2.
DataPelago is the developer of DataPelago Accelerator for Spark, a technology it said increases Apache Spark performance while reducing costs by up to 80 percent on qualifying workloads. The technology can be deployed without the need to rewrite applications or migrate data.
DataPelago Accelerator for Spark is built on that company’s GenAI-native DataPelago Nucleus engine, which the company said accelerates data processing by harnessing any available hardware from CPUs to GPUs.
NetApp said the acquisition expands the company’s portfolio with technology to enable GPU-accelerated data processing aligned directly with the storage layer.
NetApp CEO George Kurian, in a prepared statement, said, “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. 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.”
Dave Van Hoy, founder and president of Advanced Systems Group, an Emeryville, Calif.-based solution provider and NetApp channel partner, told CRN that prior to the acquisition, he had not heard of DataPelago but is looking forward to seeing it become a part of NetApp.
“I’m super excited about it because it aligns to my view of where storage is going and what’s important around that,” Van Hoy said. “That view really comes from some work I’ve been doing with IBM, who I think, ironically, is way out in front of this.”
Van Hoy explained that IBM, with which Advanced Systems Group also partners, believes in the concept of creating content-aware storage that needs to be accessed by both human end users and machines focused on AI. In both cases, he said, the problem is the same: how to find needed data as fast as possible with the least amount of friction.
“In the media space, we use a lot of things called MAMS, or media asset management systems, which are portable legacy databases that require a ton of human attention to really make useful,” he said. “And then in the general namespace world, there are some estimates that people spend as much as 20 percent of their time just trying to find the data they were looking for that they know is there somewhere and that may be relevant.”
DataPelago appears to solve the issue for both types of users, Van Hoy said.
“I think the concept of creating vectorization within the storage so that, whether it’s a machine or a human looking for data, ensuring it’s in a structure that makes the most sense to in terms of search and find is definitely the game in storage,” he said. “I think the acquisition is actually a really good move for NetApp.”
