Amazon Web Services's AI Shanghai Lablet division has created a new predictive model -- an open-source benchmarking tool called 4DBInfer used to graph predictive modeling on RDBs, a relational ...

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 ...

SAN FRANCISCO--(BUSINESS WIRE)--Cyber risk analytics leader CyberCube has launched the world’s first set of detailed Exposure Databases to enable (re)insurers and brokers to perform a wide array of ...

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 ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When Snowflake announced its $250 million acquisition of Crunchy Data two weeks ago at its ...

Enterprise AI success depends on data readiness for AI, including scalable architecture and reliable data pipelines. Vector databases enable AI systems to retrieve relevant information from large ...

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 ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

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 ...