Oracle and NVIDIA have expanded their partnership to make enterprise AI services more accessible, powerful, and practical. Announcements made during Oracle AI World cover everything from incredibly powerful new hardware to deeply integrated software aimed at putting AI at the very core of enterprise data.
NVIDIA’s Vice President of Hyperscale and High Performance Computing Ian Buck said: “Through this latest partnership, Oracle and NVIDIA are pioneering new frontiers in cutting-edge accelerated computing, streamlining database AI pipelines, accelerating data processing, powering enterprise use cases, and making it easier to deploy and scale inference in OCI.”
The highlight announcement is the new OCI Zettascale10 compute cluster. The platform is accelerated by NVIDIA GPUs and designed for AI training and inference workloads that would otherwise challenge regular servers.
OCI Zettascale10 promises powerful peak AI computing performance of 16 Zettaflops and is combined with NVIDIA’s Spectrum-X Ethernet. It’s a networking fabric specifically designed to prevent GPUs from sitting around waiting for data, allowing organizations to efficiently scale up to millions of processors.
But raw power is only half the story. The essence of this partnership is software integration aimed at weaving AI into every layer of business operations.
Mahesh Thiagarajan, Executive VP, Oracle Cloud Infrastructure, commented:
“Additionally, the native availability of NVIDIA AI Enterprise on OCI gives our joint customers access to a leading AI toolset near OCI’s 200+ cloud services to support the long tail of customer innovation.”
Give brains to your Oracle database using AI
The foundation of this new strategy is Oracle AI Database 26ai. For years, the conventional wisdom has been to move data to where the AI models reside. Oracle turns that on its head, arguing that applying AI to data is much safer and more efficient. This latest database release embodies that “AI for Data” vision.
“By architecting AI and data together, Oracle AI Database makes ‘AI for Data’ easy to learn and easy to use,” said Juan Loaiza, executive vice president of Oracle Database Technologies at Oracle.
One of the standout features is the ability to run agent AI workflows within the database. By combining a company’s private sensitive data with public information, AI agents can tackle complex problems without moving that private data outside of a secure environment. This is made possible through features such as integrated hybrid vector search that allows AI to search for context across all data types, whether it’s a relational table, a JSON file, or a spatial map.
Oracle is also clearly thinking about playing the long game with security. The new database implements NIST-approved quantum-resistant algorithms for both data in transit and at rest. This is a defense against “harvest now, decrypt later” attacks, where hackers steal encrypted data today with the goal of decrypting it on future quantum computers.
Holger Muller, Vice President and Principal Analyst at Constellation Research, commented, “Good AI requires good data. With Oracle AI Database 26ai, customers have both: a single place where their business data is current, consistent, and securely stored. And it’s the perfect place to use AI without moving that data.”
“To help simplify and accelerate AI adoption, AI Database 26ai includes great new AI capabilities that go beyond AI Vector Search. What’s notable is that Oracle is building agent AI into the database, allowing customers to build, deploy, and manage their own in-database AI agents using a no-code, visual platform that includes pre-built agents.”
The new database is designed to work in conjunction with NVIDIA’s toolset. Its programming interface can now connect directly to NVIDIA NeMo Retriever, a collection of microservices that handles the complex plumbing of modern AI for enterprises.
This makes it much easier for developers to implement things like search extension generation (RAG). Simply put, RAGs allow language models to search for relevant facts within a company’s documents before answering a question, making the response more accurate and useful.
Oracle Private AI Services Container is also powered by GPUs. This container allows businesses to run AI models in their own secure environment. You will soon be able to use the cuVS library to offload the heavy lifting of creating vector embeddings, a core task of AI search, to powerful NVIDIA GPUs. This is expected to reduce the time it takes to prepare data for AI applications.
Democratizing enterprise AI
This partnership goes beyond databases and aims to simplify the entire AI pipeline. The new Oracle AI Data Platform now includes a built-in NVIDIA GPU option and NVIDIA RAPIDS Accelerator for Apache Spark. For data scientists and engineers, this is a big problem. This means that you can use GPUs to accelerate data processing and machine learning workflows, often without changing a single line of existing code.
All of these tools and capabilities are integrated within Oracle AI Hub. Its purpose is to provide organizations with a single place to build, deploy, and manage AI solutions. From the hub, users can deploy NVIDIA’s NIM microservices, such as prepackaged AI skills, through a simple, no-code interface.
To further lower the barrier to entry, the complete NVIDIA AI Enterprise software suite is now available natively within the OCI console. This means developers can launch GPU instances and enable all the NVIDIA tools they need with just a few clicks, without going through a separate procurement process. This is a small change, but it makes a big difference in how quickly your team can get started.
It’s clear that this partnership is aimed at solving real-world challenges that businesses face when trying to implement AI. By integrating hardware, data, and software tools into one cohesive ecosystem, Oracle and NVIDIA are making the case that the era of practical, secure, and scalable enterprise AI is firmly here.
SEE ALSO: Cisco: Only 13% of companies have a solid AI strategy, leaving them behind rivals
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