2026년 엔터프라이즈 AI를 형성할 6가지 데이터 변화

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows.That stability eroded as successive waves introduced NoSQL document stores, graph databases, and most recently vector-based systems. In the era of agentic AI, data infrastructure is once again in flux — and evolving faster than at any point in recent memory.As 2026 dawns, one lesson has become unavoidable: data matters more than ever.RAG is dead. Long live RAGPerhaps the most consequential trend out of 2025 that will continue to be debated into 2026 (and maybe beyond) is the role of RAG.The problem is that the original RAG pipeline architecture is much like a basic search. The retrieval finds the result of a specific query, at a specific point in time. It is also often limited to a single data source, or at least that's the way RAG pipelines were built in the past (the past being anytime prior to June 2025