The commodification of data is driven primarily by two factors. First, its value is increasing, with more organizations ...

For companies looking to navigate the AI data center shift, success starts with smarter design, faster simulation and ...

Experts joined DBTA's latest webinar, New Database Technologies and Strategies for the AI Era, to offer their perspectives on AI-database relationship, examining best practices and new solutions.

Abstract: Distributed cloud ... In this article, retrieval and storage-based indexing framework (RSIF) is designed to improve the concurrency of user and service provider access to the cloud-stored ...

This explainer takes a look at the main ways in which large language models ... not just big theoretical existential ones – but ones which can harm people today. In this explainer, we take a closer ...

The IIoT incorporates machine learning and massively parallel distributed systems such as clouds, clusters, and grids for big data storage, processing ... first introduces a novel concentric computing ...

It eliminates duplication, improves traceability, and enhances decision-making by ensuring consistency and reducing data silos. Institutions using this model have reported 33% faster time-to-market ...

You’ll uncover how it solves persistent challenges like schema evolution, data consistency, and transactional limitations—issues that have long plagued traditional data lakes. From its ...

Forward-looking: As the world faces a data tsunami, with most information destined for long-term storage, one technology could offer a sustainable, low-maintenance alternative. Whether Cerabyte ...