Further, MongoDB is also announcing an Atlas integration with Feast. The widely-adopted open-source store provides AI and LLM apps with structured data during training and inference. This means machine learning (ML) teams can operate without having to play a “high stakes game of database musical chairs” requiring them to move data from their primary training database to a separate system for real-time inferencing, said Cefalo.
“This database sprawl doesn’t just create operational overhead, it creates drift, where the model trains on one version of reality but makes predictions on another,” he said. This can be complex and expensive, and a hurdle to scaling AI.
Finally, to support security and compliance, MongoDB is providing cross-region connectivity to MongoDB Atlas from AWS PrivateLink, which supports connectivity between AWS services, virtual private clouds (VPCs), and on-premises networks without exposing traffic to the public internet. This integration, now generally available, provides a “single, auditable model” that simplifies compliance and maintains strong security posture for organizations operating across multiple regions, Cefalo explained.
