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Oracle Database@Azure for AI and Machine Learning: Architecture, Benefits, and Best Practices

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Oracle Database@Azure for AI and Machine Learning Workloads - Using Azure's AI stack while keeping Oracle as the trusted system of record — the architecture, the patterns, and the trade-offs. 📅 July 29, 2026     🏷️ Oracle DB@Azure,   AI, ML, Microsoft Fabric, Vector Search, RAG        ⏱ 24 min read Article Overview Enterprise AI keeps stalling on the same problem: the models live in one place and the trustworthy data lives in another. For most large organisations that data — the orders, claims, policies, and transactions that describe the actual business — sits in Oracle. This article is about closing that gap without moving the system of record. It shows how to keep Oracle as the authoritative source on Oracle Database@Azure while putting the full Azure AI stack to work on that data: zero-ETL mirroring into Microsoft Fabric, native vector search inside the database, retrieval-augmented generation grounded in operational rows, and agents bu...
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Performance Tuning Oracle Databases on Azure: Best Practices, Tools, and Optimization Techniques

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Performance Tuning Oracle Databases on Azure A method that starts from wait events — CPU and ECPU sizing, storage design, indexing, SQL tuning, AWR and ASH, and monitoring. 📅 July 28, 2026            🏷️ Oracle Database@Azure,  Performance Tuning       ⏱ 25 min read Article Overview Most performance work fails for the same reason: it starts with a guess. Someone adds an index, bumps a memory parameter, or throws more CPU at a database because those are the levers within reach — before knowing what the database was actually waiting on. This guide takes the opposite approach. It starts from the evidence — wait events, AWR, and ASH — and only then moves to the fix, whether that is CPU and ECPU sizing, Exadata-aware storage design, indexing, or rewriting a bad statement. Everything is code-first: the queries to find the problem, read the report, and prove the fix. It is written for Oracle Database@Azure specifically, where the Exadata ...
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