Is `timestamp > now() - 30s` valid in every SQL engine?
No. The intent is valid, but syntax differs by engine. Use PostgreSQL `NOW() - INTERVAL '30 seconds'`, MySQL `NOW() - INTERVAL 30 SECOND`, and SQLite `datetime('now', '-30 seconds')` patterns.
timestamp > now() - 30s in 2026
If you searched for timestamp > now() - 30s, you are usually trying to pull only fresh events from a stream, queue, webhook log, or analytics table. The core idea is right, but production-safe SQL in 2026 needs explicit interval syntax and clear timestamp units. Most systems fail when one service emits milliseconds while the database comparison expects seconds.
The fastest way to avoid false negatives is to keep UTC timestamps as native date/time columns, not strings, and to document window boundaries as either inclusive or strict. This keeps alerting, retries, and dashboard counts aligned when your traffic spikes.
Quick 2026 engine patterns
- PostgreSQL: `created_at >= NOW() - INTERVAL '30 seconds'`
- MySQL: `created_at >= NOW() - INTERVAL 30 SECOND`
- SQLite: `created_at >= datetime('now', '-30 seconds')`
- Validate sample values in a converter before shipping query changes.
Related pages on EpochConverter
Start with WHERE timestamp > now() - 30s for syntax context, then review SQL timestamp > now() - 30s and PostgreSQL last-30-seconds.
To validate raw epoch values from your query output, use the main epoch converter tool.
Related developer tool
If this query is part of a recurring job, verify your cadence with Cron Expression Builder.
Frequently Asked Questions
Should this query use UTC timestamps?
Yes. Keep stored timestamps in UTC and compare with UTC-aware functions to avoid timezone drift and daylight-saving issues.
Why do last-30-second filters miss fresh rows?
The usual causes are comparing milliseconds against seconds, querying text fields instead of timestamp columns, and server clock skew.
Should I use `>` or `>=` for a 30-second window?
Use `>=` if the boundary must be inclusive. Use `>` if you need a strict cutoff. Pick one rule and keep it consistent in jobs and dashboards.