Jörg Schad explains how to tame the complex "data management hairball" to build scalable, safe architectures for AI. He ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Artificial Intelligence (AI) agents based on Retrieval-Augmented Generation (RAG) technology are rapidly proliferating. RAG ...

AkasicDB integrates vector, graph, and relational stores within a single DBMS, and processes queries across the three data models as a single execution plan through an unified query planner and ...

I’ve seen a lot of promising AI prototypes fall apart after launch. And it’s rarely because the model was bad. More often, the problem starts much earlier; teams treat the data layer like something ...

I've been thinking a lot lately about what it actually takes to make an AI agent genuinely useful for database work, both for administration and for application access to the data tier. Writing the ...

A slew of product announcements highlighted that Confluent is bigger and stronger as part of IBM, and that CIOs are having to rethink data operations in order to deliver AI-driven business strategies.

Try the Interactive Demo, VLDB 2026 — explore GenDB's full pipeline with a guided audio walkthrough. See how six AI agents analyze data, design storage, plan execution, generate code, and optimize it ...

SQL, the Structured Query Language, is a cornerstone skill for anyone working with data. To master this powerful language, consistent practice is crucial. We present a curated list of 12 top-notch ...

DataStax, an IBM company, provides integrated AI dev platforms that let you harness data in your app without building a complex tool stack. Interacting with databases often requires a level of ...