When should I use ORM (encode/orm) instead of SQLAlchemy?

Lightweight async ORM with a clean Django-inspired API for FastAPI and Starlette projects. Type-annotated models with async query support in a minimal, easy-to-configure package. Simple database-backed microservices that do not need the full power of SQLAlchemy

When should I use SQLAlchemy instead of ORM (encode/orm)?

Complex relational database work requiring both high-level ORM and low-level SQL control. Applications that must support multiple database backends from a single codebase. Production data engineering pipelines that need fine-grained control over SQL generation

What are the main weaknesses of ORM (encode/orm)?

Very limited feature set compared to SQLAlchemy async or Tortoise ORM. Small community with few tutorials and limited long-term documentation. Largely superseded by SQLAlchemy async and Tortoise ORM for async Python projects

What are the main weaknesses of SQLAlchemy?

Steep learning curve for the 2.0 API, especially async patterns and type-annotated models. Verbose boilerplate for simple CRUD operations compared to lighter ORMs like Peewee. Bulk insert and update performance requires explicit optimization to match raw SQL

ORM (encode/orm) vs SQLAlchemy: Key Differences for Python Data Engineering

ORMs for Python

ORM (encode/orm)

Lightweight Async ORM

★ 4.3

BSD-3-Clause

pip install orm

SQLAlchemy

Python SQL Toolkit & ORM

★ 4.9

MIT

pip install sqlalchemy

Side-by-Side Comparison

ORM (encode/orm)

SQLAlchemy

ORM (encode/orm)

SQLAlchemy

Best For

✓Lightweight async ORM with a clean Django-inspired API for FastAPI and Starlette projects
✓Type-annotated models with async query support in a minimal, easy-to-configure package
✓Simple database-backed microservices that do not need the full power of SQLAlchemy

✓Complex relational database work requiring both high-level ORM and low-level SQL control
✓Applications that must support multiple database backends from a single codebase
✓Production data engineering pipelines that need fine-grained control over SQL generation

Best For

✓Lightweight async ORM with a clean Django-inspired API for FastAPI and Starlette projects
✓Type-annotated models with async query support in a minimal, easy-to-configure package
✓Simple database-backed microservices that do not need the full power of SQLAlchemy

✓Complex relational database work requiring both high-level ORM and low-level SQL control
✓Applications that must support multiple database backends from a single codebase
✓Production data engineering pipelines that need fine-grained control over SQL generation

Weaknesses

•Very limited feature set compared to SQLAlchemy async or Tortoise ORM
•Small community with few tutorials and limited long-term documentation
•Largely superseded by SQLAlchemy async and Tortoise ORM for async Python projects

•Steep learning curve for the 2.0 API, especially async patterns and type-annotated models
•Verbose boilerplate for simple CRUD operations compared to lighter ORMs like Peewee
•Bulk insert and update performance requires explicit optimization to match raw SQL

Weaknesses

•Very limited feature set compared to SQLAlchemy async or Tortoise ORM
•Small community with few tutorials and limited long-term documentation
•Largely superseded by SQLAlchemy async and Tortoise ORM for async Python projects

•Steep learning curve for the 2.0 API, especially async patterns and type-annotated models
•Verbose boilerplate for simple CRUD operations compared to lighter ORMs like Peewee
•Bulk insert and update performance requires explicit optimization to match raw SQL

License

BSD-3-Clause

MIT

License

BSD-3-Clause

MIT

Install

pip install orm

pip install sqlalchemy

Install

pip install orm

pip install sqlalchemy

Rating

★ 4.3

★ 4.9

Rating

★ 4.3

★ 4.9

Key Features

ORM (encode/orm)

1Async ORM built on SQLAlchemy Core for use with Starlette and FastAPI
2Supports PostgreSQL (asyncpg), MySQL (aiomysql), and SQLite (aiosqlite)
3Simple Model class with async `all()`, `get()`, `create()`, and `filter()` methods
4Integrates with Alembic for schema migrations
5Lightweight — minimal abstraction over raw SQL for predictable behavior

SQLAlchemy

1Dual-layer API: high-level ORM and low-level Core SQL expression language
2Dialect system supports PostgreSQL, MySQL, SQLite, Oracle, MSSQL, and more
3Connection pooling and transaction management out of the box
4Alembic migration integration for schema versioning
5Async support via `asyncio` and `asyncpg` for non-blocking queries

How Python Data Engineers Use These Tools

ORM (encode/orm)

Python data engineers building async data APIs with FastAPI or Starlette use the `databases` (Encode ORM) library to perform non-blocking database operations. It replaces synchronous `psycopg2` calls with awaitable async queries, keeping the event loop unblocked during database I/O in high-concurrency ingestion endpoints.

SQLAlchemy

SQLAlchemy is the standard Python database toolkit for data engineers. The Core layer is used to construct and execute SQL queries programmatically — building dynamic INSERT/UPDATE statements, managing connection pools in long-running services, and reading query results into pandas DataFrames via `pd.read_sql()`. The ORM layer manages schema-as-code in application codebases.

More ORMs for Python Comparisons

ORMs for Python

Django ORM vs SQLAlchemy

ORMs for Python

Peewee vs SQLAlchemy

ORMs for Python

Pony ORM vs SQLAlchemy

ORMs for Python

SQLAlchemy vs SQLObject

ORMs for Python

SQLAlchemy vs Tortoise ORM

ORMs for Python

Gino vs SQLAlchemy

Individual Tool Pages

View ORM (encode/orm) details →View SQLAlchemy details →

Side-by-Side Comparison

ORM (encode/orm)

SQLAlchemy

ORM (encode/orm)

SQLAlchemy

Best For

✓Lightweight async ORM with a clean Django-inspired API for FastAPI and Starlette projects
✓Type-annotated models with async query support in a minimal, easy-to-configure package
✓Simple database-backed microservices that do not need the full power of SQLAlchemy

✓Complex relational database work requiring both high-level ORM and low-level SQL control
✓Applications that must support multiple database backends from a single codebase
✓Production data engineering pipelines that need fine-grained control over SQL generation

Best For

✓Lightweight async ORM with a clean Django-inspired API for FastAPI and Starlette projects
✓Type-annotated models with async query support in a minimal, easy-to-configure package
✓Simple database-backed microservices that do not need the full power of SQLAlchemy

✓Complex relational database work requiring both high-level ORM and low-level SQL control
✓Applications that must support multiple database backends from a single codebase
✓Production data engineering pipelines that need fine-grained control over SQL generation

Weaknesses

•Very limited feature set compared to SQLAlchemy async or Tortoise ORM
•Small community with few tutorials and limited long-term documentation
•Largely superseded by SQLAlchemy async and Tortoise ORM for async Python projects

•Steep learning curve for the 2.0 API, especially async patterns and type-annotated models
•Verbose boilerplate for simple CRUD operations compared to lighter ORMs like Peewee
•Bulk insert and update performance requires explicit optimization to match raw SQL

Weaknesses

•Very limited feature set compared to SQLAlchemy async or Tortoise ORM
•Small community with few tutorials and limited long-term documentation
•Largely superseded by SQLAlchemy async and Tortoise ORM for async Python projects

•Steep learning curve for the 2.0 API, especially async patterns and type-annotated models
•Verbose boilerplate for simple CRUD operations compared to lighter ORMs like Peewee
•Bulk insert and update performance requires explicit optimization to match raw SQL

License

BSD-3-Clause

MIT

License

BSD-3-Clause

MIT

Install

pip install orm

pip install sqlalchemy

Install

pip install orm

pip install sqlalchemy

Rating

★ 4.3

★ 4.9

Rating

★ 4.3

★ 4.9

Key Features

ORM (encode/orm)

1Async ORM built on SQLAlchemy Core for use with Starlette and FastAPI
2Supports PostgreSQL (asyncpg), MySQL (aiomysql), and SQLite (aiosqlite)
3Simple Model class with async `all()`, `get()`, `create()`, and `filter()` methods
4Integrates with Alembic for schema migrations
5Lightweight — minimal abstraction over raw SQL for predictable behavior

SQLAlchemy

1Dual-layer API: high-level ORM and low-level Core SQL expression language
2Dialect system supports PostgreSQL, MySQL, SQLite, Oracle, MSSQL, and more
3Connection pooling and transaction management out of the box
4Alembic migration integration for schema versioning
5Async support via `asyncio` and `asyncpg` for non-blocking queries

How Python Data Engineers Use These Tools