For R&D leaders evaluating AI investments, I’d offer one piece of advice: Before spending more on models, look hard at your ...

The gap between human and AI performance on database tasks will shrink over time, but more complex problems will still ...

The addition of Transformational Modeling, Tx, allows data teams to simplify, automate, and collaborate on their end-to-end data modeling workflows. SAN FRANCISCO--(BUSINESS WIRE)--SqlDBM, a leading ...

Google wants Gemini, its family of generative AI models, to power your app’s databases — in a sense. At its annual Cloud Next conference in Las Vegas, Google announced the public preview of Gemini in ...

MCP Is great, but it isn’t the whole AI answer ...

Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

As businesses shift toward smarter digital infrastructures, the database landscape is rapidly evolving. Siva Prasad Nandi, a researcher in cloud-native technologies, explores the rise of serverless ...

IEEE research highlights multi-model databases outperform single-model systems, reducing AI costs, latency, and schema issues ...

Data models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity. Data modeling is the process through which we ...

While relational databases rely on rigid structures, document databases are much more natural to work with and can be used for a variety of use cases across industries. A document database (also known ...