Measure
Read the statistics your database already keeps for every query: executions, total time, rows read. QueryInsights records the change on each poll, so every execution counts once. Nothing sits in your traffic path.
QueryInsights sits beside your databases, learns from what actually runs, and turns that into specific, ready-to-ship recommendations.
QueryInsights sits beside your database, learns from the queries that actually run, and only recommends changes it has tested against your real workload.
Read the statistics your database already keeps for every query: executions, total time, rows read. QueryInsights records the change on each poll, so every execution counts once. Nothing sits in your traffic path.
Queries collapse into patterns with their literals removed, ranked by total database time. Noise you don't control, like a Spark job or BI tool, can be ignored with a rule.
Candidate index changes are tested on a workload twin with production's statistics. The optimizer costs your whole top-N workload, and any change that slows a query is rejected.
Get the proven change set with every affected query's plan before and after, plus AI rewrites for individual slow queries, grounded in your real schema.
QueryInsights is a side-car for your databases — it observes, learns, and serves up advice. Nothing in the request path. Nothing for your application to integrate.
QueryInsights observes from the side. It never proxies your application traffic, so there's no risk to latency or availability.
Every recommendation is generated against the actual definitions of the tables a query touches, not a generic textbook example.
By normalizing queries to their pattern shape, the same fix solves a thousand variants — and you stop chasing duplicate noise.
QueryInsights is in early access. Tell us a little about your workload and we'll be in touch.
Or email us at bhargav.akhani@queryinsights.dev