Oracle’s multicloud approach: Put the database wherever AI pipelines already run
Enterprises racing to put AI agents into production are learning that real-time data pipelines matter as much as the models. An agent working from a stale subset of corporate records delivers far less than one wired into live, mission-critical data. That shift is changing how companies decide where their databases run. Oracle Corp. has pushed […] The post Oracle’s multicloud approach: Put the…
Enterprises are racing to integrate AI agents into production, realizing that real-time data pipelines are as crucial as the models themselves. Oracle Corp. has expanded its database modernization strategy to other clouds, with customers increasingly positioning their databases adjacent to the applications and AI pipelines they are constructing.
At Oracle AI World, Nathan Thomas, senior vice president of product management for Oracle Cloud Infrastructure, explained that customers are defining their AI pipelines with a focus on trust and security, asking themselves how to bring mission-critical data into these pipelines. Oracle offers its database on its own cloud, via on-premises Cloud@Customer, as well as within Amazon Web Services (AWS), Microsoft Azure, and Google Cloud.
Customers typically do not ask which cloud to choose; instead, they opt for the cloud where their applications and AI pipelines already reside. Oracle's strategy of running the same Exadata hardware across all environments simplifies migration and avoids the need for extensive refactoring. Thomas highlighted that moving from on-premises Exadata to the cloud on the same hardware eliminates most challenges traditionally associated with database migrations.
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