Watch this episode in video format on Spotify!If you're building Python applications on MongoDB and still writing raw queries by hand, you're leaving a lot of developer productivity on the table. Beanie, the async-first ODM built on Pydantic, was created to fix exactly that — and this episode goes deep on how and why it works.You'll learn how Beanie maps Python objects to MongoDB documents without sacrificing atomicity or performance, why async-first design matters for modern Python stacks, how schema migrations actually work in a document database, and what the deprecation of Motor means for your existing codebase. The episode also covers Beanie's integration with FastAPI, how it handles indexes and aggregation pipelines under the hood, and what's coming in the next phase of the library.Ramon, the creator of Beanie and a senior software engineer at Microsoft, built this library five years ago to fill a gap nobody else had addressed. He's joined by Shubham, MongoDB's product manager for Python client libraries, for a live demo and Q&A.Follow The MongoDB Podcast so you never miss an episode.-[00:00] Introduction & Guest Welcome[01:00] What Is Beanie? The ODM Explained[04:10] ODM vs ORM — What's the Difference?[05:20] Why Ramon Built Beanie (The Origin Story)[06:30] Core Design Principles: Atomicity & Async-First[08:00] FastAPI + MongoDB: The Rising Python Stack[11:00] Bonnet: The Synchronous Beanie Backport[12:55] Live Demo: Defining Document Schemas with Pydantic[16:00] Nested Documents, Links & Polymorphic Collections[18:45] Best Practices for Schema Design[20:30] Index Management in Beanie[22:40] Complex Queries: Beanie vs Raw PyMongo[24:30] Aggregation Pipelines in Beanie[28:05] Schema Migrations: Forward, Backward & Freefall[31:30] Motor Is Deprecated — What That Means for You[34:00] Beanie v2: What Changed and What Didn't[36:20] FastAPI, Flask & Django Integration[37:45] What's Next for Beanie: Performance & Lambda Optimization[39:30] How to Contribute to Beanie[41:00] Resources, Community & Audience Q&A

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