In today's data-driven landscape, businesses face an unprecedented explosion of diverse data types, necessitating a vast array of database options to handle specific workloads. This has resulted in a ...

The database world is getting a bit muddied when it comes to managing data variety. Not so long ago, with the exception of a few leading database management system (DBMS) platforms, databases ...

Relational foundation model NVIDIA Kumo Relational beats XGBoost and AutoGluon across 41 benchmark tasks on enterprise ...

Business demands a single view of data, and IT strains to cobble together data from multiple data stores to present that view. Multi-model databases, however, can help you integrate data from multiple ...

San Francisco-based Monte Carlo Data, a company providing enterprises with automated data observability solutions, today announced new platform integrations and capabilities to expand its coverage and ...

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 ...

Picture this: The year is 2030, and you’re living in a world where retailers can predict consumer behavior with uncanny accuracy, healthcare providers are diagnosing diseases before symptoms escalate ...

AI-ready data platforms, vector databases, and scalable infrastructure allow businesses to turn raw data into reliable AI ...

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 ...

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 ...