By Margo Harrell,Hemant Suri
Publication Date: 2026-05-05 00:00:00
Initial results from private technical preview customers show the real potential of this approach.
These results are not incremental improvements. They signal a fundamental shift in the way companies can approach data-intensive workloads – performance improvements and cost reductions are no longer a trade-off, but a combined result. As data volumes grow and AI adoption accelerates, this type of step-change improvement is quickly transitioning from a competitive advantage to a business imperative.
IBM has also implemented this innovation internally through its CIO organization, acting as “client zero” for GPU-accelerated watsonx.data. In early deployments, IBM teams achieved up to 25x faster query performance by running IBM watsonx.data Presto C++ with GPU acceleration compared to CPU-only execution 1 At the same time, the cost of this workload is reduced by approximately 80% due to the shorter running time 2. These results demonstrate not only the scalability of the approach, but also the benefits of IBM…