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Gartner recommends new measures to defend against AI-generated data in the enterprise.
The database is no longer just where data lives, but where context gets assembled. And in AI, context is everything.
Analysts say the acquisition positions ClickHouse to help enterprises run AI more reliably and transparently by pairing high‑performance analytics with native LLM observability tools.
The ability to write parts of SQL queries in natural language will help developers speed up their work, analysts say.
Ahana commits to the development of Meta’s Velox Open Source Project, extending engineering resources and naming significant contributors.
Google Cloud’s lead engineer for databases discusses the challenges of integrating databases and LLMs, the tools needed to overcome these challenges, and how AI-native databases will help bridge the gap.
We need to stop trying to build ‘God-tier’ agents that can do everything and start building ‘intern-tier’ agents that do one thing perfectly.
Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform discipline. Enterprises that succeed with RAG rely on a layered architecture.
The company advises customers to upgrade immediately, or if they can’t, to disable zlib compression.
AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.