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

Google Cloud Summit came to London last week, and we took the opportunity to sit down with database execs Sailesh ...

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, ...

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; ...

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Data can exist in any number of different places across an enterprise. Gathering all that data for analysis in IT operations and security is often a challenging task. The overall goal is to make it ...

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 ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.