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PostgreSQL Glossary

VACUUM

A PostgreSQL maintenance operation that reclaims storage and updates statistics for optimal performance. Example: VACUUM ANALYZE users; reclaims space fro…

Definition

A PostgreSQL maintenance operation that reclaims storage and updates statistics for optimal performance.

What VACUUM Means in PostgreSQL

A PostgreSQL maintenance operation that reclaims storage and updates statistics for optimal performance.

VACUUM appears frequently in production operations, architecture decisions, and troubleshooting workflows. Understanding this term helps teams reason about reliability, performance, and safe change management.

Why VACUUM Matters

Teams that understand VACUUM 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

VACUUM ANALYZE users; reclaims space from deleted rows and updates table statistics for the query planner.

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

Vector Search Vela ACID Atomicity Archiving (WAL Archiving) archive_command archive_mode BYOC (Bring Your Own Cloud)

Frequently Asked Questions

What is VACUUM in PostgreSQL?
A PostgreSQL maintenance operation that reclaims storage and updates statistics for optimal performance.
Why is VACUUM important?
VACUUM matters because it directly affects how teams build, operate, and recover PostgreSQL systems in production.
Can you give a practical VACUUM example?
VACUUM ANALYZE users; reclaims space from deleted rows and updates table statistics for the query planner.
How does VACUUM relate to backup, recovery, or performance?
In most production deployments, VACUUM influences one or more of these areas: data safety, restore behavior, and performance under load.
What should teams check first when implementing VACUUM?
Start with clear operational goals, test in a non-production environment, and validate behavior with repeatable runbooks before relying on it in production.