Transforming Ideas into Innovation with Cloud, AI, and Data

  I have a small confession: I have never been fond of security metaphors borrowed from construction. We talk about firewalls, perimeters, gates, moats, and now, increasingly, vaults. The trouble is that most of these analogies stopped being accurate decades ago. A real-world vault is a heavy steel box that does exactly one thing — it keeps people out. An Oracle Database Vault, on the other hand, is a programmable policy engine baked into the kernel of an AI database, deciding in microseconds who is allowed to do what, from where, with which credential, on which row of which table. So while I am not entirely sold on the name, the thing behind it has quietly become one of the more interesting pieces of database security on the market — and with the Oracle AI Database 26ai release it has been pushed into a new role that the original 2006-era Database Vault (introduced in Oracle Database 10g Release 2) was never designed for: protecting data against AI agents that can write their own...

Enterprise cloud journeys keep running into the same gravity well: mission-critical Oracle databases that must be modernized without sacrificing performance, availability, or regulatory posture. Oracle Database@Azure —delivered through the jointly engineered Oracle Exadata Database Service on Azure —closes that gap. It places real Exadata infrastructure inside Microsoft Azure data centers, so workloads can stay Oracle-native while applications move freely across the Azure stack. 1. What is Oracle Exadata on Azure? Oracle Exadata Database Service on Azure is a co-engineered offering from Microsoft and Oracle that provisions Exadata infrastructure inside Azure data centers and exposes it through the Azure portal, CLI, ARM templates, and Terraform . In practice, customers get the same Exadata platform that powers Oracle Cloud Infrastructure (OCI), but billed, governed, and networked as a first-class Azure resource. The result is a unified operating model: Oracle continues to run on the pl...

 The release of Oracle AI Database 26ai marks a significant evolution—not just for AI inside the database, but also for Oracle Real Application Clusters (RAC) . While the core RAC architecture remains consistent with 23ai, 26ai introduces AI-driven intelligence, automation, and resilience improvements that directly enhance clustered database environments. This blog explores the key RAC-relevant innovations and how they reshape high availability, scalability, and performance. 1. AI-Native RAC – Intelligent Cluster Operations Oracle 26ai transforms RAC into an AI-aware platform : Built-in AI models and vector capabilities run directly inside the database No need to move data to external AI engines Supports semantic search and embeddings across RAC nodes his means: AI workloads can scale horizontally across RAC nodes Reduced data movement → lower latency and higher efficiency Oracle calls this shift an AI-native database architecture , embedding intelligence directl...