Comparing
High-level concurrency and networking framework on top of asyncio or Trio
Official MongoDB driver for Python — insert, query, update, and aggregate documents with a Pythonic API.
| Metric | anyio | pymongo |
|---|---|---|
| Ecosystem | Python | Python |
| Difficulty | Beginner ✓ | Intermediate |
| Weekly downloads | 0 | 3.5M↑ |
| Latest version | v4.13.0 | v4.10.1 |
| Recipes | 1 | 2↑ |
anyio only
Shared
pymongo only
Use anyio when writing an async library or framework that you want to be runtime-agnostic. It's also useful in applications that want trio's structured concurrency model but need to interop with asyncio-based libraries like FastAPI or aiohttp.
Applications already using MongoDB, document-oriented data (nested objects, variable schemas), rapid prototyping where schema flexibility matters, storing unstructured data like logs or events.
For application code that commits to asyncio (e.g. a FastAPI app), using asyncio directly is simpler — there's no need for the compatibility layer. anyio shines at the library level, not the application level.
When you need strong ACID transactions across many documents (use PostgreSQL), when your data is highly relational, or when you want an ORM-style interface (use Motor + Beanie for async).
anyio
pymongo