AI database deep dive: Oracle’s platform redesign

At Oracle World in Las Vegas in October, Oracle Corp. founder and CEO Larry Ellison got right to the point. “AI changes everything,” Ellison told attendees, and his company’s recent releases have reflected the transformation taking place in the AI database world.

Oracle has taken a major step into AI database architecture, with a redesigned Oracle Database and the unveiling of the AI Data Platform at its Las Vegas event. Oracle’s releases represent a re-engineering of its core offerings to facilitate customer access to any major AI model by connecting proprietary data. Storage is now a platform for reasoning and enterprise data fuels intelligence to drive the business.

“Oracle is in a unique position with respect to enterprise AI,” said Dave Vellante, chief analyst at theCUBE Research. “Organizations realize they can’t just throw LLMs at the opportunity without a solid data infrastructure. Specifically, a strong database foundation with modern capabilities like vector search and the ability to handle multiple data types. On April 14, we’ll be digging into the key aspects of enabling enterprise AI and specifically how Oracle is approaching AI innovation while addressing AI safety.”

Reporting from the New York Stock Exchange, theCUBE’s Oracle Data Deep Dive NYC event explores how Oracle is embedding machine learning, vector search and advanced analytics directly into its data platform — and how multicloud integration, lakehouse modernization and governance enable production-ready architectures at scale. (* Disclosure below.)

Get a preview of what to expect from theCUBE’s event coverage:

New capabilities for the AI database

Ellison’s remarks at Oracle World last fall were accompanied by the launch of AI Database 26ai and Oracle Autonomous AI Lakehouse, both designed to support artificial intelligence training and inference across cloud and on-premises environments. These latest solutions highlighted Oracle’s interest in a strategy that integrates AI capabilities into its core data platforms.

AI functions were natively embedded into the database engine for application support, eliminating the need for moving data separately. The new capabilities also included support for Model Context Protocol servers, which enable AI-to-AI communication. Also included were vector search and a methodology for deploying AI agents inside the database.

Juan Loaiza, executive vice president of database technology at Oracle, spoke with theCUBE at the time of the new releases and emphasized that his firm’s AI Database was not simply a way to join the AI marketing parade, but represented a foundational redesign for the company. The aim was to make life easier for enterprise customers interested in performing semantic searches and running AI queries without the need for external tools or databases.

“We put a lot of new technologies for AI in there, and then moving on all the way into Lakehouse … and running AI queries against the existing database,” Loaiza said. “We have over a hundred projects in AI in this release of the Oracle Database. It’s a fresh new database that’s been completely infused with AI, not just in one place, but throughout the entire stack.”

Stricter data privacy enforcement

Widespread adoption of AI in the enterprise has also raised security to new levels of importance. Oracle has responded to this need by moving privacy enforcement into the database layer itself.

The goal is to prevent data leakage by design, an important requirement for enterprise customers who must ensure compliance in the handling of sensitive financial or medical information.

“The AI only sees the data that the end user is allowed to see,” Loaiza told theCUBE. “It’s the same thing with a lot of other business rules like data integrity, data locking, data validation, and data evolvability. With the AI generating it, and you must guarantee it, it’s much better to move those capabilities into the database where we can guarantee it underneath the AI.”

Oracle has also taken steps to safeguard data against future threats from quantum computers, which are developing the ability to rapidly decrypt protective algorithms. Enhancements include quantum-safe encryption for both data at rest and data in flight based on government-approved algorithms.

Oracle has pursued a roadmap for AI that leverages its decades of database expertise with integration channels for open agent frameworks and widely used large language models. In early March, the company reported a 44% surge in revenue, easing fears that AI might be impacting its software business.

“If it can maintain its growth and revenue momentum while containing its capex, that’s a good sign,” said Valoir analyst Rebecca Wettemann in a recent conversation with SiliconANGLE. “The good news is that with the autonomous database, Oracle can deliver on AI infrastructure at a lower cost and greater efficiency than some of its competitors.”

TheCUBE event livestream

Don’t miss theCUBE’s coverage of the Oracle Data Deep Dive NYC event on April 14. Plus, you can watch theCUBE’s exclusive content on-demand after the event.

How to watch theCUBE interviews

We offer you various ways to watch theCUBE’s coverage of the Oracle Data Deep Dive NYC event, including theCUBE’s dedicated website and YouTube channel. You can also get all the coverage from this year’s events on SiliconANGLE.

TheCUBE podcasts

SiliconANGLE’s “theCUBE Pod” is available on Apple Podcasts, Spotify and YouTube, which you can enjoy while on the go. During each podcast, SiliconANGLE’s John Furrier and Dave Vellante unpack the biggest trends in enterprise tech — from AI and cloud to regulation and workplace culture — with exclusive context and analysis.

SiliconANGLE also produces our weekly “Breaking Analysis” program, where Dave Vellante examines the top stories in enterprise tech, combining insights from theCUBE with spending data from Enterprise Technology Research, available on Apple Podcasts, Spotify and YouTube.

Guests

During the Oracle Data Deep Dive NYC event, don’t miss insights from Oracle executives and industry experts shaping the future of enterprise AI. Conversations will focus on how Oracle is embedding machine learning, vector search and advanced analytics into its data platform, while also addressing multicloud integration, lakehouse modernization, governance and data privacy. Guests will offer perspectives on how these capabilities are helping enterprises build production-ready AI architectures that are more scalable, secure and closely tied to business outcomes.

(* Disclosure: TheCUBE is a paid media partner for the Oracle Data Deep Dive NYC event. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Image: SiliconANGLE