Databricks says it solved the decades-old data pipeline problem that's been slowing AI agents

Databricks says new products LTAP and Lakehouse//RT unify transactional and analytical data for AI agents, delivering ...
The Financial

Why Enterprises Need AI Query Engines to Fuel Agentic AI

Data is the fuel of AI applications, but the magnitude and scale of enterprise data often make it too expensive and time-consuming to use effectively. According to IDC’s Global DataSphere 1, ...
dbta

Achieving Data Warehouse Query Performance on the Data Lake with CelerData

The move to the data lakehouse was full of promises—speed, agility, and cost-effective query performance, to name a few. Yet, many enterprises find it difficult to realize all these benefits at once; ...
InfoQ

Redis Improves Performance of Vector Semantic Search with Multi-Threaded Query Engine

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Trust3 AI Delivers One Policy Layer for the Agentic, Multi-Engine Lakehouse

Trust3 AI today announced the latest release of its centralized data access governance platform at the Databricks Data + AI ...
InfoWorld

Next-gen data engines transform metadata performance

New data engine architectures such as Speedb boost metadata performance, reduce latency, accelerate search time, and optimize CPU consumption. Here’s how. The rapid growth of data-intensive use cases ...
Search Engine Land

From search to answer engines: How to optimize for the next era of discovery

The shift from traditional search engines to AI-powered answer engines signals more than a technical upgrade. It marks a fundamental change in how people discover, evaluate, and act on information.