Five Minute Briefing - Data Center
June 2, 2025
Five Minute Briefing - Data Center: June 2, 2025. Published in conjunction with SHARE Inc., a bi-weekly report geared to the needs of data center professionals.
News Flashes
GridCARE, a new company "powering the AI revolution," is emerging from stealth to boost data center capacity. The company closed a highly oversubscribed $13.5 million Seed financing round led by Xora, a deep technology venture capital firm backed by Temasek.
IBM has updated its LinuxONE mainframes, using the same hardware as its new z17 mainframe platform but designed to run on Linux operating systems, with the focus on artificial intelligence. The LinuxONE Emperor 5 is the fifth generation of IBM LinuxONE iron and comes three years after the release of the last generation. The new Emperor has been updated for improved security, cost-efficiency, and AI acceleration of mission-critical enterprise workloads.
DataStax announced its acquisition by IBM is officially closed, allowing the companies to "scale to new heights" and accelerate production AI and NoSQL data at scale. With Astra DB, Hyper-Converged Database, and now watsonx.data, DataStax will provide seamless access to both unstructured and structured data for production AI, according to the company.
Lumen Technologies and IBM are partnering to develop enterprise-grade AI solutions at the edge—integrating watsonx, IBM's portfolio of AI products, with Lumen's Edge Cloud infrastructure and network. Together, Lumen and IBM aim to bring powerful, real-time AI inferencing closer to where data is generated, helping companies overcome cost, latency, and security barriers as they scale AI adoption and enhance customer experiences, according to the companies.
Think About It
In the realm of data modeling, many-to-many relationships are often considered an "odd duck." Unlike one-to-one or one-to-many relationships, which can be directly implemented in physical database schemas, many-to-many relationships must remain in the abstract, the conceptual, the supernatural, and never the physical. This insubstantial nature makes them troublesome for greener data modelers.