Structured Query Language

SQL, structured query language, is the standard language for defining and manipulating data in relational databases. A query describes the desired result rather than the steps to compute it, and the database's query planner decides how to execute it using available indexes and statistics. The core operations are SELECT to read, INSERT, UPDATE, and DELETE to modify, and JOIN to combine rows across tables, with GROUP BY and window functions supporting aggregation and analytics. Transactions provide atomic, consistent, isolated, and durable changes, which is why financial and operational systems still rely on relational databases. PostgreSQL, MySQL, and SQLite dominate operational workloads, while Snowflake and BigQuery apply the same language to analytical warehouses. PostgreSQL's extension model, including pgvector for embedding search, has made it a common single store for both application data and AI retrieval. Text-to-SQL features now let a model translate a plain-language question into a query, giving non-engineers direct access to data, though generated queries still need review against the actual schema. The usual performance trap is a query that scans an entire table because no index supports its filter or join, which stays fast on test data and degrades sharply as rows accumulate.