In this article, we explore how to design and implement multitenant database architectures tailored for B2B SaaS applications. You’ll learn how to securely isolate data, scale your backend efficiently, and choose the right multitenancy strategy.

Learn how to go beyond simple schema changes and manage real data transformations with Alembic migrations. This post covers practical techniques for updating enums, denormalizing tables, and handling complex data updates.

Learn how to master SQLAlchemy’s eager loading techniques,joinedload, selectinload, and subqueryload, to eliminate the N+1 problem and write high-performance Python backend code.

A deep dive into SQLAlchemy’s modern declarative mapping using registry() and as_declarative_base(). Learn how to structure scalable, maintainable model layers for Python backend projects.

A practical deep dive into optimistic vs. pessimistic locking in ORMs, covering real-world patterns, common pitfalls, and how to use database locks effectively with PostgreSQL and SQLAlchemy.