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PostgreSQL Glossary

SQL (Structured Query Language)

A standardized language for managing and manipulating relational databases. Example: SELECT name FROM users WHERE created_at > '2023-01-01' retrieves user…

Definition

A standardized language for managing and manipulating relational databases.

What SQL (Structured Query Language) Means in PostgreSQL

A standardized language for managing and manipulating relational databases.

SQL (Structured Query Language) appears frequently in production operations, architecture decisions, and troubleshooting workflows. Understanding this term helps teams reason about reliability, performance, and safe change management.

Why SQL (Structured Query Language) Matters

Teams that understand SQL (Structured Query Language) can make better decisions on database design, incident response, and release safety.

In modern PostgreSQL environments, this concept often connects directly to backup strategy, performance tuning, and operational confidence.

  • Improves decision quality for production operations
  • Reduces avoidable troubleshooting time
  • Strengthens reliability and recovery planning

Practical Example

SELECT name FROM users WHERE created_at > '2023-01-01' retrieves users created this year.

Where To Learn More

You can explore deeper implementation patterns in the Vela articles library, review platform workflows in How Vela Works, and compare approaches in our PostgreSQL comparisons.

Related Glossary Topics

Supabase Standby Signal ACID Atomicity Archiving (WAL Archiving) archive_command archive_mode BYOC (Bring Your Own Cloud)

Frequently Asked Questions

What is SQL (Structured Query Language) in PostgreSQL?
A standardized language for managing and manipulating relational databases.
Why is SQL (Structured Query Language) important?
SQL (Structured Query Language) matters because it directly affects how teams build, operate, and recover PostgreSQL systems in production.
Can you give a practical SQL (Structured Query Language) example?
SELECT name FROM users WHERE created_at > '2023-01-01' retrieves users created this year.
How does SQL (Structured Query Language) relate to backup, recovery, or performance?
In most production deployments, SQL (Structured Query Language) influences one or more of these areas: data safety, restore behavior, and performance under load.
What should teams check first when implementing SQL (Structured Query Language)?
Start with clear operational goals, test in a non-production environment, and validate behavior with repeatable runbooks before relying on it in production.