How PostgreSQL and MySQL Handle No-Op Updates: A Performance Deep Dive
Introduction
No-op updates in SQL—where an UPDATE statement sets columns to their existing values—are rare in well-designed applications. Yet legacy code, third-party plugins, or complex business logic can trigger these operations. Understanding how PostgreSQL and MySQL handle no-op updates is crucial for database architects and performance engineers, as it impacts disk usage, transaction logs, and overall efficiency.
What Is a No-Op Update?
A no-op update occurs when your SQL UPDATE statement doesn’t change any data.
UPDATE customers SET status = 'active' WHERE id = 7;
If customer #7 already has status = ‘active’, this is a no-op update. But what do PostgreSQL and MySQL actually do behind the scenes?
PostgreSQL: MVCC and Row Versions
PostgreSQL uses Multi-Version Concurrency Control (MVCC), which creates a new row version for every UPDATE—including no-op updates. The old row becomes a “dead tuple.”
Example Workflow:
- You insert a row.
- You issue a no-op UPDATE.
- PostgreSQL increments the “dead tuple” count, bloating your storage.
Why It Matters:
Frequent no-op updates can trigger table bloat, requiring regular VACUUM maintenance and impacting query performance.
Pro Tip
Monitor pg_stat_get_live_tuples and pg_stat_get_dead_tuples to track table bloat.
MySQL InnoDB: Smart Change Detection
In contrast, MySQL InnoDB checks whether the data will actually change:
- If the new values match the old, no new row versions are created.
- No entries are added to the undo log, reducing disk I/O and storage use.
UPDATE customers SET status = 'active' WHERE id = 7; -- No change detected, no data modified, no undo log entry created.
Why It Matters:
MySQL’s smart update detection means less disk churn and no unnecessary storage bloat.
Performance Implications
| Feature | PostgreSQL | MySQL InnoDB |
|---|---|---|
| Row Version/Dead Tuple | Created for every update | Only if data actually changes |
| Undo Log Entries | Yes | No for no-op |
| Transaction Log Growth | Higher risk for bloat | More efficient |
| Table Bloat | Possible | Avoided |
| Concurrency | MVCC overhead | Minimal with no-op |
Best Practices for Avoiding No-Op Updates
- Avoid unnecessary updates in application code—use WHERE clauses strategically.
- Run VACUUM regularly on PostgreSQL tables to reduce dead tuple bloat.
- Monitor update patterns to prevent storage and performance bottlenecks.
Conclusion
Seemingly harmless no-op updates can have serious consequences—especially in PostgreSQL. For database architects and DevOps teams, understanding how each system handles these operations helps optimize resources, maintain high performance, and plan maintenance schedules more effectively.
MinervaDB offers expert consulting, support, and managed services to help you prevent table bloat and ensure optimal database performance for PostgreSQL, MySQL, and more.
Let us know if you’d like a deep dive on VACUUM strategies or profiling undo log growth in enterprise workloads!
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Further Reading:
- Troubleshooting MariaDB Performance
- MariaDB 2025 High Availability Best Practices
- Advanced Database Performance Tuning for MariaDB
- Next-Gen Data Management
- Understanding Database Locking
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