MongoDB’s document data model allows software applications to know the difference (and importance) between different types of data from simple key-value pairs, to rich data and hierarchical objects.

Conversely, translating document models, with their hierarchical and nested data structures, has traditionally been more challenging. So, is now the time for MongoDB to take the analytics plunge?

It's understandable that those new to MongoDB - a so-called 'schema free' database - might assume that they no longer need to be concerned with the art-science of data modeling. However, in reality ...

The integration offers users a way to augment generative AI models with their own data to ensure their applications are grounded in up-to-date context.

Historically, Databricks, MongoDB and Snowflake appealed to different audiences, but recent moves are starting to breach those silos.

Available in 48 Azure regions globally, MongoDB Atlas provides joint customers with the powerful capabilities of the document data model.

Expanded partnership between MongoDB and Google Cloud enables developers to use state-of-the-art AI foundation models from Google to build new classes of generative AI applications with expert ...

MongoDB is well-positioned to capitalize on the increasing demand for AI workloads with its non-relational database. Find out why MDB stock is a Buy.