A curated set of links for Azure Cosmos DB, Azure DocumentDB, and the open-source DocumentDB project.
Guidance for building globally distributed apps, tuning performance/cost, and exploring AI + vector search scenarios.
Read the official docs for guidance, tutorials, and reference material.
High-level overview, core concepts, and when to use Cosmos DB.
Run Cosmos DB locally for development and testing.
Learn about vector indexing and vector search for AI/RAG scenarios.
Reliability, security, performance, and cost guidance for production apps.
Patterns and sample content for Azure Cosmos DB.
Samples, tools, and community projects from the Cosmos DB team.
Tutorials, use cases, and event recordings.
Hands-on learning module for building AI-driven apps with Cosmos DB for NoSQL.
Learn about Azure DocumentDB, how it relates to Cosmos DB, and how to migrate workloads.
What Azure DocumentDB is, how it scales, and compatibility details.
Common questions about features, pricing, and how it relates to Cosmos DB.
Track service updates, new features, and notable changes over time.
Compare scaling model, cost model, global distribution, and query focus.
Migration guidance for moving from Cosmos DB for MongoDB (vCore) to Azure DocumentDB.
Explore and run the open-source DocumentDB engine that powers Azure DocumentDB.
Overview of the open-source DocumentDB project and how it works.
Run DocumentDB locally using Docker and connect with psql.
The open-source DocumentDB engine source code (MIT-licensed).
Project homepage for the open-source DocumentDB ecosystem.