SQL

SQL stands for Structured Query Language and is the standard programming language used to manage and manipulate relational databases. It allows developers to create, read, update, and delete data (CRUD operations) while maintaining strict relationships between data stored in structured tables.

SQL databases are schema-based, meaning the structure of the data must be defined before use. This approach ensures consistency, reliability, and support for complex queries, making SQL databases the backbone of many enterprise systems and transactional applications.

Advanced

SQL supports features such as joins, indexes, stored procedures, triggers, and views to handle large-scale queries and optimise performance. It is used across relational database management systems such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.

SQL databases emphasise ACID compliance, ensuring atomicity, consistency, isolation, and durability of transactions. Advanced techniques include query optimisation, database normalisation, and partitioning for scalability.

Relevance

• Provides reliable and consistent handling of structured data.
• Supports complex queries for analytics and reporting.
• Ensures strong data integrity through ACID compliance.
• Backed by decades of adoption in mission-critical systems.

Applications

• Managing customer and order records in e-commerce.
• Handling financial transactions in banking systems.
• Powering enterprise applications with strict data integrity needs.
• Running business intelligence and analytics queries.

Metrics

• Query execution time and performance under load.
• Database normalisation efficiency.
• Transaction throughput and latency.
• Storage utilisation and indexing performance.

Issues

• Less flexible for unstructured or rapidly changing data.
• Vertical scaling can be costly compared to distributed systems.
• Performance may degrade with very large datasets without optimisation.
• Requires careful schema design to prevent inefficiencies.

Example

A retail chain uses PostgreSQL, an SQL database, to manage customer orders and inventory. By leveraging ACID-compliant transactions, the system ensures that stock levels remain accurate across multiple locations, reducing errors and improving operational efficiency.