Data engines ready for AI.
Overview
To transform your enterprise, AI agents need continuous access to your data, putting strain on data infrastructure not designed for agentic reasoning loops.
With NVIDIA infrastructure, enterprises can meet the new volume and velocity of data demands from AI while leveraging their existing data stack. For CPU-based data processing, including analytics, real-time streaming, batch, and online transaction processing (OLTP), NVIDIA Vera delivers the per-core performance and high-bandwidth memory that agentic workloads need. For the fastest speed at scale, NVIDIA CUDA-X™ libraries accelerate the most popular data engines on GPUs, providing agents with on-demand access to structured data in tables and unstructured data living as PDFs, emails, images, and videos across the enterprise.
The accelerated computing platform delivers up to a 20x GPU speedup for data processing, while NVIDIA Vera brings a high-performance CPU platform, enabling enterprises to take action faster with new use cases.
By running on the NVIDIA optimized stack, organizations have saved 80% in costs or more, helping your data infrastructure do more with less.
The world’s most popular analytics and vector data engines have drop-in accelerators to make adoption straightforward, including Apache Spark, OpenSearch, and more.
With context from 90% of enterprise data stored in PDFs, messages, and emails with NVIDIA cuVS, and ground truth from terabytes of structured data processed in minutes with NVIDIA cuDF, your data is ready for agentic AI.
Products
NVIDIA libraries, tools, and models power the data processing ecosystem with GPU acceleration, delivering faster data workloads and pipelines at enterprise scale.
Adopters
From analytical SQL queries to vector search, organizations are adopting NVIDIA's accelerated computing platform into their existing data platforms to accelerate AI-ready pipelines.
Resources