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). Those limitations have led a growing conga line of vendors all claiming that RAG is dying, on the way out, or already dead.What is emerging, though, are alternative approaches (like contextual memory), as well as nuanced and improved approaches to RAG. For example, Snowflake recently announced its agentic document analytics technology, which expands the traditional RAG data pipeline to enable analysis across thousands of sources, without needing to have structured data first. There are also numerous other RAG-like approaches that are emerging including GraphRAG that will likely only grow in usage and capabilities in 2026.So now RAG isn’t (entirely) dead, at least not yet. Organizations will still find use cases in 2026 where data retrieval is needed and some enhanced version of RAG will likely still fit the bill.
Enterprises in 2026 should eva …