Agentic workflows are making distributed, always-on databases nonnegotiable

Enterprise database infrastructure is undergoing its most consequential redesign in decades, as agentic AI workloads demand a level of elasticity that legacy architectures were never built to provide.

As AI becomes deeply embedded in mission-critical workflows, organizations are learning that the underlying data platform can no longer be an afterthought. The pressure is especially urgent as agentic processes generate machine-speed transaction volumes across multi-region, multicloud deployments, according to Wei Hu (pictured), senior vice president of high-availability technologies at Oracle Corp.

“Oracle customers have always asked us for an always-on, no-downtime database system,” Hu told theCUBE. “Such a system needs to survive failures of the server, the machine room, data center, region and cloud. What the Oracle Globally Distributed AI Database does is take this one step further using two technologies. First, we make the whole replicated topology look like a single logical database, so instead of looking at databases with primary peers, replicas and so forth, you see one logical database from the application, as well as from administration. That’s number one. The second thing that we do is provide strong consistency.”

Hu spoke with theCUBE’s Dave Vellante at the Oracle Data Deep Dive NYC event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Globally Distributed AI Database redefines availability for agentic workloads. (* Disclosure below.)

Database infrastructure built for distributed, always-on AI

The technical architecture underpinning Oracle’s availability claims represents a significant departure from conventional replication models. Oracle’s Exadata Exascale offering uses Raft replication — a consensus-based protocol — to ensure that commits are durably recorded across a majority of nodes before completing, enabling sub-three-second automated failover designed to deliver zero data loss, Hu explained.

“With the Raft protocol, we just need the majority to agree on the change,” he said. “The leader is one member, so I just need one follower to agree with me. When I move changes to both in parallel, as soon as the first follower gets the data, I can move ahead — because now I got the majority of who has the data. That means I’m traveling at the [speed of] the fastest follower instead of the slowest follower.”

Agentic AI adds a new dimension of urgency to these database infrastructure demands. Because agents run at machine speed — booking transactions, executing trades and triggering downstream workflows without human latency — they generate burst loads that are both enormous and highly dynamic, Hu said. The distributed architecture’s hyperscale vector index support is equally critical: By aggregating in-memory capacity across up to a thousand nodes, the system keeps vector search response time constant even as datasets grow, which directly determines how smart an agentic application can become.

“In AI, the name of the game is the more data you have, the smarter you are,” Hu said. “This massive scaling out of in-memory vector indexes allows you to make very, very smart agentic AI applications.”

Rounding out the database infrastructure platform is Oracle True Cache, an in-memory, self-managing cache that automatically propagates backend database changes to the cache tier without application intervention — eliminating the staleness and some of the manual synchronization complexity of application-managed solutions such as Redis, according to Hu. A key use case is data sovereignty: True Cache can be deployed in a region close to the application tier to deliver local-speed access to data that regulation requires to be stored elsewhere.

“True Cache and the Globally Distributed AI Database can actually work together to give you a data tier that is extremely available, extremely scalable and can give you great latency — and also, of course, absolute consistency,” Hu said. “Whatever services you depend upon have to be available. I think recent events have shown us that to be available, you need to be located in multiple locations. Globally distributed is becoming mandatory for businesses.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Oracle Data Deep Dive NYC event:

(* Disclosure: TheCUBE is a paid media partner for the Oracle Data Deep Dive NYC event. Neither Oracle, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE