. The goal here is to write efficient, modular code that handles complex tasks—like calculating a discount or authenticating a password—without slowing down the user experience. 3. The Memory: Data Management Data is the lifeblood of any application. Backend engineers must choose the right storage solution: Relational Databases (SQL): Like PostgreSQL or MySQL, used for structured data where consistency is key (e.g., banking). Non-Relational Databases (NoSQL): Like MongoDB, used for flexible, high-speed data storage (e.g., real-time chats). Caching: Tools like Redis are used to store frequently accessed data in memory, dramatically reducing latency. 4. Scalability and Availability A great backend doesn't just work; it stays working under pressure. As more users join, the system must scale. This involves
Utilizes GET, POST, PUT, DELETE for CRUD operations. Payloads: Typically exchanges data via JSON or XML formats. gRPC (Google Remote Procedure Call) backend engineering fundamentals
Tools that let you interact with databases using code instead of raw SQL (e.g., SQLAlchemy, Sequelize, Hibernate, Prisma). The Memory: Data Management Data is the lifeblood