Features: AI is redrawing the enterprise software stack, turning applications into agents, data into context, and workflows ...

The so-called modern data stack is getting a facelift and perhaps a complete body makeover. As the point of control shifts from the database management system to the governance layer, we cite three ...

An increasingly loud transformation has been reshaping how operations-heavy companies think about data infrastructure. In 2026, I believe it could fundamentally reshape three vendor categories. For ...

Input from theCUBE and data practitioner communities suggests that acceleration in compute performance and the sophistication of the modern data stack is outpacing the needs of many traditional ...

Debate and discussion around data management, analytics, BI and information governance. DeepSeek’s recent developments have ignited significant discussion in the AI community. DeepSeek is very ...

As CTO, you know when the current code base is too old: it takes forever to get new features out, response time for end-users is slow, tools are outdated, etc. Yet these issues barely trigger a raised ...

“Emerging applications such as deep neural network demand high off-chip memory bandwidth. However, under stringent physical constraints of chip packages and system boards, it becomes very expensive to ...

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.

This online data science specialization is for software engineers interested in the principles of building and architecting large software systems that use big data. The first course introduces you to ...

The headless data architecture is the formalization of a data access layer at the center of your organization. Encompassing both streams and tables, it provides consistent data access for both ...