SQLAlchemy

SQLAlchemy excels where it matters most in production: connection pooling is robust with multiple pool implementations (QueuePool, NullPool, etc.), configurable overflow/timeout behavior, and proper connection recycling. The engine.dispose() pattern makes graceful shutdowns trivial. Echo logging gives you query-level observability without custom instrumentation, and event hooks let you inject metrics at every lifecycle point.

The 2.0 release was a major breaking change but dramatically improved async support and type safety. Migration pain was real but worth it - the new syntax reduces N+1 queries by making lazy loading explicit. Memory usage is predictable with proper session management; the session-per-request pattern with scoped_session works flawlessly under load. Statement caching is automatic and effective.

Error handling is transparent - connection failures surface immediately with clear exceptions, and you control retry logic. Pool timeouts are configurable (default 30s can be aggressive). The Core API gives you an escape hatch when ORM overhead matters, and compiled query caching dramatically improves throughput on repeated queries.

SQLAlchemy has been rock-solid in production across multiple high-traffic services. The connection pooling is configurable down to the finest details - pool_pre_ping catches stale connections, pool_recycle handles server-side timeouts, and QueuePool behavior under load is predictable. Engine.dispose() makes graceful shutdowns straightforward. The event system provides hooks for query timing, connection checkout/checkin, and error handling without monkey-patching.

The 2.0 migration was painful but worth it. Breaking changes were well-documented, and the migration guide is comprehensive. The new syntax eliminates implicit behaviors that caused subtle bugs in 1.x. Performance improved noticeably - bulk inserts with RETURNING clauses are faster, and the new Result API reduces memory overhead for large result sets.

Error handling is excellent - SQLAlchemy wraps database-specific exceptions into a hierarchy you can catch consistently. The echo flag and logging integration make debugging straightforward. Under load, connection pool exhaustion fails fast with clear TimeoutError messages. Default timeouts are sensible but you'll want to tune pool_timeout and connect_timeout for your workload.

SQLAlchemy has been my go-to for database work across dozens of production applications. The Core query construction API uses bound parameters by default, making SQL injection virtually impossible if you use the API correctly. The text() construct requires explicit bindparams, which forces you to think about parameterization. Exception handling is clean and doesn't leak sensitive connection details in production—just configure logging appropriately.

The 2.x series improved type safety significantly, catching many potential bugs at development time. Connection pooling is solid with sensible defaults, and the engine handles TLS/SSL configuration cleanly when passed through connection strings or connect_args. I appreciate that it doesn't try to do authentication itself—it delegates to the underlying database driver, keeping that complexity where it belongs.

The biggest security win is how it handles user input: the ORM and Core APIs make it natural to write safe queries. You have to actively work against the framework to introduce injection vulnerabilities. Error messages in production are informative without exposing schema details if you configure SQLAlchemy's logging properly.