Comparison with Alternatives

Feature Matrix

Feature	Dynantic	PynamoDB	Raw boto3
Type Safety	Pydantic v2	Custom types	Dict-based
IDE Autocomplete	Excellent	Good	Limited
Query DSL	Pythonic	Pythonic	Dict-based
Batch Operations	Yes	Yes	Yes
Transactions	Yes	Yes	Yes
TTL Support	Auto-convert	Yes	Manual
Polymorphism	Yes	No	No
Auto-UUID	Yes	No	No
Async Support	No (use threadpool)	No	No (use aioboto3)
Maturity	Beta	Stable	AWS Official

When to Use Dynantic

• You use Pydantic and want DynamoDB integration
• You're building Lambda functions or sync applications
• You want IDE autocomplete with Pydantic validation
• You need single-table design with polymorphism
• You value developer experience and clean DSL

When to Use PynamoDB

• You want a mature, battle-tested library
• You prefer a custom type system over Pydantic
• You don't need Pydantic's validation features

When to Use Raw boto3

• You need maximum control and flexibility
• You have simple use cases with few models
• You want AWS's official SDK with guaranteed compatibility

When to Use aioboto3

• You need native async/await support
• You're building async applications (aiohttp, FastAPI with async endpoints)
• You're willing to manage async client lifecycle

Limitations

Feature	Status	Notes
Async support	Not planned	Use asyncio.to_thread() or aioboto3
Streams	Not planned	Use AWS Lambda triggers
PartiQL	Not planned	Use standard query API
Auto-migrations	Not planned	Manage tables with IaC (Terraform, CDK)

Design Constraints

• No relationships — DynamoDB doesn't support joins
• No schema enforcement — DynamoDB is schemaless (Pydantic validates on read/write)
• Cursor opacity — Pagination cursors are plain dicts (not cryptographically signed)