Overview
New Data Demands
To transform your enterprise, AI agents need continuous access to your data, putting strain on data infrastructure not designed for agentic reasoning loops.
By accelerating unstructured and structured data processing with NVIDIA cuDF and NVIDIA cuVS, enterprises can meet the new volume and velocity of data demands from AI, while leveraging the data infrastructure they've invested in for years.
The world's most popular data engines run on the accelerated computing platform—helping agents access structured data living in tables and unstructured data living as PDFs, emails, images, and videos across the enterprise.
Benefits
Transform Your Data for AI
Massive Performance Gains
The accelerated computing platform delivers up to 20x speedup for data processing, enabling enterprises to take action faster with new use cases.
Significant Cost Savings
By running on the NVIDIA optimized stack, organizations have saved 80% in costs or more, helping your data infrastructure do more with less.
Easy to Adopt
The world’s most popular analytics and vector data engines have drop-in accelerators to make adoption straightforward, including Apache Spark, OpenSearch, and more.
AI-Ready Data
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
CUDA-X for Data Processing
cuDF and cuVS are CUDA-X™ toolkits, built on highly optimized CUDA® primitives, to accelerate the data processing ecosystem.
Adopters
Data Processing Ecosystem
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.
Data Processing on NVIDIA Vera
For enterprises running agentic AI workloads at scale, AI agents dramatically increase concurrent, continuous small-scale querying of structured enterprise data. NVIDIA Vera has 1.2 TB/s of memory bandwidth and high-speed on-chip fabric that offers the per-core performance, high throughput, and predictability under load that supports the increased volume and velocity of queries. For the Starburst analytics engine, NVIDIA Vera processed queries 3x faster compared to x86, reducing query execution from minutes to seconds, while the Redpanda streaming engine saw a 6x improvement in p99 versus x86, enhancing the reliability of the data engine.
Coming soon.
Resources
The Latest in Data Processing
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