Data modeling is the blueprint that transforms raw information into structured, usable insights. By defining entities, relationships, and rules, it connects business needs to technical implementation.

MongoDB Inc. is making its play for the hearts and minds of artificial intelligence developers and entrepreneurs with today’s announcement of a series of new capabilities designed to help developers ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

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

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

Oracle announced a suite of agentic AI capabilities integrated directly into Oracle AI Database, enabling AI agents to securely access enterprise data where it already exists, rather than requiring ...

As frontier models converge, the advantage in enterprise AI is moving away from the model and toward the data it can safely access. For most enterprises, that advantage lives in unstructured data: the ...

SurrealDB Inc. today revealed that it has raised an additional $23 million in funding for its multimodel artificial intelligence-native database. The plan is to accelerate product maturity and ...

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 ...