Oracle's MultiCloud database revenue exploded 1,529% in a single quarter, while its $455B revenue backlog (+359% YoY) proved enterprise AI demand isn't hype—it's contracted business spanning years.

In their latest quarter, Oracle booked so much long-term demand that remaining performance obligations (RPO) hit $455B.

The earnings impact was so significant that Oracle jumped ~40% on the results, pulled other AI stocks with it, and made Larry Ellison the world's richest person.

Contracted demand, not pipeline

“We signed four multi-billion-dollar contracts with three different customers in Q1, This resulted in RPO contract backlog increasing 359% to $455 billion…” - said Oracle CEO, Safra Catz

This is booked revenue.

Growth is still concentrated among a few top customers, but in the coming month they expect to sign more customers with RPO “likely to exceed half-a-trillion dollars”.

Oracle broke down the entire OCI projected revenue until 2030 in black and white, because “most of the revenue in this 5-year forecast is already booked”:

$18B in FY26 (+77%) → $32B → $73B → $114B → $144B by FY30

Multi-cloud strategy delivered breakthrough results

"MultiCloud database revenue from Amazon, Google and Microsoft grew at the incredible rate of 1,529% in Q1," highlighted Larry Ellison.

They “expect MultiCloud revenue to grow substantially every quarter for several years as we deliver another 37 data centers to our three Hyperscaler partners, for a total of 71.”

This isn't competition with AWS, Azure, and Google Cloud - it's strategic collaboration and embedding Oracle's database layer in the dominant cloud platforms.

You can buy them via cloud marketplaces and this will count towards your cloud commits. E.g. Oracle Database@Azure counts toward MACC commits.

Infrastructure trumps apps for Oracle

OCI revenue hit $3.3B (+55%) while applications grew just 11%. Oracle is betting on AI-ready infrastructure and database services powering enterprise AI workloads.

Its upcoming AI Database will let customers use Google's Gemini, OpenAI's ChatGPT, xAI's Grok, etc. directly on existing Oracle databases. Rather than forcing costly data migrations, Oracle brings AI models to where enterprise data already lives.

“Oracle AI Cloud Infrastructure and the Oracle MultiCloud AI Database will both contribute to dramatically increasing cloud demand and consumption over the next several years.”

“AI Changes Everything,” stressed Larry Ellison

Key takeaways:

• Collaborate and embed vs compete

• Data gravity drives AI adoption

• Infrastructure leads software for now

Oracle's $455B backlog now rivals other hyperscalers combined.

Their insight: enterprise AI transformation isn't about choosing clouds - it's making AI accessible wherever customers and their data reside.