The Ground Beneath the Database
From attached disks to a shared, elastic foundation—the story of disaggregating MongoDB and turning a database you manage into one you consume. Summary On September 29th, MongoDB announced the public preview of Atlas…
Topic - Edition
MongoDB
Intelligent Workload Management: Keeping Your Clusters Available When It Matters
Modern applications need to stay available even when traffic spikes suddenly or queries consume disproportionate resources. MongoDB Atlas is designed for high availability, but availability in practice is about more…
Code Mode Without the Interpreter: Agents That Write Aggregation Pipelines
Standfirst Code mode gives an AI agent a code interpreter and lets it write real programs—one round trip instead of five, filtering where the data lives instead of in the context window. It also means running arbitrary…
Data Modeling and Schema Design for MongoDB Search Part 2: Use Cases and Patterns
This is Part 2, continuing from “Part 1: Practical Considerations.” In Part 1, the foundational concerns were laid out. Here in Part 2, common use cases and patterns to address them with best practices are covered.…
Data Modeling and Schema Design for MongoDB Search Part 1: Practical Considerations
Data modeling in MongoDB is the art and science of organizing data in a database to represent entities, attributes, and relationships, thereby optimally supporting business objectives. There are three types of data…