A relational database organizes data into structured tables and defines relationships between them. The core components include tables, columns, rows, primary keys, foreign keys, and indexes. Tables represent entities (e.g., “Users” or “Orders”) and consist of columns (attributes like “UserID” or “OrderDate”) and rows (individual records). Primary keys uniquely identify rows within a table (e.g., a unique “UserID” in the “Users” table). Foreign keys link tables by referencing primary keys in related tables (e.g., “OrderID” in an “Orders” table pointing to a “UserID”). Indexes improve query performance by enabling faster data retrieval for specific columns.
Another critical component is the schema, which defines the structure of the database, including table layouts, data types (e.g., integers, strings), and constraints (e.g., “NOT NULL” to enforce required fields). Constraints ensure data integrity: for example, a “UNIQUE” constraint on an “Email” column prevents duplicate entries. Relationships between tables are categorized as one-to-one, one-to-many, or many-to-many. For instance, a one-to-many relationship exists between “Users” and “Orders” (one user can place many orders). Many-to-many relationships often require junction tables (e.g., a “ProductOrders” table linking “Products” and “Orders”).
Finally, SQL (Structured Query Language) is used to interact with the database. It allows developers to perform CRUD operations (Create, Read, Update, Delete) and manage transactions. For example, a SELECT query retrieves data, while JOIN clauses combine data from related tables. Transactions ensure atomicity (all operations succeed or fail together) and consistency (e.g., deducting funds from one account and crediting another atomically). Stored procedures or views can encapsulate complex logic, such as generating monthly sales reports. Together, these components enable efficient data storage, retrieval, and management while maintaining accuracy and reliability.