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Data Processing Solutions Data Processing Data engines ready for AI. Overview Benefits Products Adopters Resources Next Steps Overview Benefits Products Adopters Resources Next Steps Overview Benefits Products Adopters Resources Next Steps Overview The Data Foundation for Agentic AI 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. Accelerating Data Processing for AI Agents Watch the GTC Berlin keynote to explore how NVIDIA’s latest advances in accelerated computing, data processing, and retrieval help enterprises put their data to work for AI agents. Watch Keynote Power Data Processing and Retrieval With NVIDIA Vera CPU Explore how European cloud providers and system builders are adopting the NVIDIA Vera CPU to support data processing, retrieval, and AI agent workloads. Learn More Benefits Transform Your Data for AI Massive Performance Gains 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. 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 NVIDIA Accelerates Data Processing NVIDIA libraries, tools, and models power the data processing ecosystem with GPU acceleration, delivering faster data workloads and pipelines at enterprise scale. cuDF for Structured Data Accelerates analytics engines on NVIDIA GPUs Includes drop-in accelerators for Apache Spark, Presto, Polars, and DuckDB Executes analytical queries in minutes from hours Learn More About cuDF cuVS for Unstructured Data GPU-accelerated vector search and index building for RAG and AI pipelines Integrates with OpenSearch, Elastic, Milvus, and more Reduces vector index build times from hours to minutes Learn More About cuVS NVIDIA Kumo Structured Leaderboard-winning structured data models for tabular, relational, and time series data Forecasts outcomes, scores risk, detects anomalies, and generates recommendations with a single foundation model Cuts time to prediction from months to seconds, without feature engineering or task-specific machine learning pipelines Try the Models NVIDIA Nemotron Retriever Open, leaderboard-winning models that set a new accuracy-efficiency frontier, giving agents the right context with fewer tokens Parses, embeds, and reranks text, images, and complex documents, including PDFs, tables, and charts Lowers agentic cost by 40 percent, reduces incorrect answers by 24 percent, and increases throughput by 2.4x Try the Models NVIDIA Auto Ontology Open-source library that generates a starter enterprise ontology from databases, documentation, metadata, and query history Enables business stewards to test, refine, and certify business meaning, giving agents governed context and provenance Delivers up to 90 percent faster ontology creation, 80 percent less time connecting data, and 10x more accurate AI queries Try the Library 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. Resources The Latest in Data Processing Blogs Sessions Videos Hardware Datasheets Power Data Processing and Retrieval With NVIDIA Vera CPU Explore how European cloud providers and system builders are adopting NVIDIA Vera CPU to support data processing, retrieval, and AI agent workloads. Learn More NVIDIA cuDF and cuVS Adopted by World's Leading Data Platforms NVIDIA's accelerated computing platform is fueling modern enterprise data processing. Integrated with the world's most widely used open source data engines—downloaded over 200 million times monthly by developers—these libraries are harnessed across enterprise data platforms, databases, and data lakes. Learn More How Snap Scaled A/B Testing With NVIDIA cuDF Snap processes 10+ petabytes daily for A/B testing across 940M+ users. Accelerating Apache Spark with NVIDIA cuDF on Google Cloud delivered 4x faster runtimes and 76% cost savings. Learn More Accelerating Large-Scale Analytics With Velox and NVIDIA cuDF IBM and NVIDIA integrate cuDF with the Velox execution engine, enabling GPU-native query execution for Presto and Apache Spark—delivering up to 12x faster analytics than CPU-only systems. Learn More Accelerating Data Processing for AI Agents Watch Jensen Huang describe how the NVIDIA Vera CPU delivers higher performance and efficiency to run 3x faster SQL analytics with Starburst and increase the reliability of real-time data streaming with Redpanda by up to 6x. Watch Keynote IBM Reinvents Data Processing IBM watsonx.data SQL analytics engine Presto is accelerated by cuDF for 5x speedup and 83% cost savings. Watch Demo Processing 100 Million Rows of Data in Under 2 Seconds With Polars Polars GPU Engine executes polars code on GPUs for massive speedups. Watch Demo Data Processing on NVIDIA Vera With NVIDIA-designed Olympus cores, 1.2 TB/s of memory bandwidth, and a high-speed on-chip fabric, NVIDIA Vera gives agentic AI the per-core performance, data throughput, and predictable performance under load required for data processing workloads, with up to 3x faster SQL analytics and 6x lower p99 latency in real-time data streaming workloads. Coming soon. Learn More Data Processing on NVIDIA RTX PRO 6000 Blackwell Server Edition NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are engineered for intensive data processing and AI workloads, delivering up to 42X speed ups and eliminating pipeline bottlenecks for data at terabyte scale. Learn More Petabyte-Scale Data Processing on NVIDIA RTX PRO 4500 Blackwell Server Edition NVIDIA RTX PRO™ 4500 Blackwell Server Edition accelerates enterprise-scale data processing with NVIDIA cuDF, delivering up to 8x faster Apache Spark queries than CPU-only systems for AI and agentic applications. This enables universal acceleration from the data center to the edge. Learn More Next Steps Ready to Learn More? Get the latest on data processing news, content, and events. Stay Informed cuDF Open source toolkit for structured data using GPU parallelism and memory bandwidth to accelerate data processing and analytics workflows. Get Started With cuDF cuVS Open source library for unstructured vector search and data clustering that enables faster vector searches and index builds. Get Started With cuVS Sign up to receive data science news Welcome back. Not you? Log Out Welcome back. Not you? Clear form AWS With NVIDIA cuDF, AWS delivers 3x faster Apache Spark performance on Amazon EMR using Amazon EC2 G7e instances on NVIDIA RTX PRO™ 4500 BSE GPUs, and AWS OpenSearch can now build billion-scale vector databases in under an hour with cuVS acceleration. Read the Blog Dell AI Data Platform Dell AI Data Platform with NVIDIA unifies Dell high-performance storage and computing infrastructure with NVIDIA accelerated computing, software, and libraries to power data processing for enterprise-scale agentic AI workflows with up to 12x speedup for vector indexing and 3X for data processing with cuDF and cuVS. Read the Blog Google Cloud Google Cloud and NVIDIA deliver GPU-accelerated analytics on G4 VMs, with Snap achieving 76% daily cost savings using Apache Spark accelerated by cuDF on GKE. Read the Blog HPE With NVIDIA Vera in HPE ProLiant Compute DL394 Gen12, HPE servers can run data processing workloads with the performance and consistency required for agentic AI workloads. Read the Press Release IBM watsonx.data IBM watsonx.data accelerated Presto with NVIDIA cuDF on A100s to execute Nestle’s queries on terabytes of global operations data 5x faster with 83% cost savings. Read the Press Release Oracle Oracle AI Database integrates NVIDIA cuVS and NVIDIA GPUs to accelerate vector index generation by up to 10x, helping enterprises build and refresh indexes faster for semantic search, RAG, and agentic AI applications grounded in governed enterprise data. Read the Blog Redpanda Redpanda’s real-time data streaming engine alternative to Apache Kafka delivers 6x lower p99 latencies on NVIDIA Vera, delivering the consistent performance enterprises need for their agentic AI workloads. Read the Blog Starburst On NVIDIA infrastructure, Starburst’s Trino-powered platform runs up to 3x faster on NVIDIA Vera compared to x86 on 1 terabyte of data and up to 7x faster on NVIDIA RTX PRO 6000, supporting agentic analytics for gathering the ground truth of the enterprise. Read the Press Release Redpanda On NVIDIA Vera, Starburst’s Trino-powered platform runs up to 3x faster compared to x86 on 1 terabyte of data, supporting AI agents gathering the ground truth of the enterprise. Read the Blog ClickHouse Running ClickHouse on NVIDIA Vera: Is your favorite database up to the challenge? Read the Blog Cloudera Powered by NVIDIA cuDF, Cloudera Data Engineering on Cloudera Anywhere Cloud offers GPU acceleration for Apache Spark without code rewrites. This enables data teams to lower cloud costs and prepare AI-ready data up to 4x faster than traditional CPU infrastructure. 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