A comprehensive new review argues that database architecture, not just algorithms, determines how successfully entity ...

Context becomes leverage when an application can connect current data, relationships, history and permissions in real time to ...

In today’s evolving technological landscape, a solid understanding of the progression of data and application architecture is an important part of the technology leader’s role. By embracing modern ...

TiDB is a prime example of an intrinsically scalable and reliable distributed SQL database architecture. Here’s how it works. In the good old days, databases had a relatively simple job: help with the ...

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 ...

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. “It’s amazing to see some of these technologies come back around,” Serra said.

Many people believe data architecture and information architecture are one and the same. But this misconception among data management leaders and their teams results in poorly designed architectures ...

Data architecture is a discipline that documents an organization's data assets, maps how data flows through IT systems and provides a blueprint for managing data. Its goal is to ensure that data is ...

Embracing modern architecture is now a necessity for staying competitive and innovative. Automation of high-quality data is at the forefront of modern data architecture, with security and flexibility ...

To meet the needs of the digital economy of the 2020s, data architecture has evolved into a dif­ferent animal than it was 10, or even 5, years ago. Most notably, there are three trends that have ...

<?xml encoding="utf-8" ?> Palantir Technologies Inc. PLTR is widely treated as an artificial-intelligence stock, but one defense AI CEO says its real strength is the “plumbing” around AI models, not ...

The increase in data flow and storage capacity demand has prompted more enterprises to use autonomous data management.