At a glance
Query Latency p50 (ms) is the median end-to-end execution time across all queries in the selected window: half of your queries finish faster than this number, half finish slower. It is the steadiest read on “what does a typical query feel like right now?” Unlike p95 or p99, p50 ignores the slow tail and tracks the bread-and-butter experience of dashboards, scheduled loads, and interactive worksheets.
Calculation
Calculated automatically from your Snowflake account state. See the At a glance summary above for what the metric tracks and the reconcile pointer below for the native check.What it tracks
This card reports the 50th percentile of query latency for the selected period, derived fromTOTAL_ELAPSED_TIME in the QUERY_HISTORY view of the SNOWFLAKE.ACCOUNT_USAGE schema (and the lower-latency INFORMATION_SCHEMA.QUERY_HISTORY table function for the live read). Although the card is labelled in milliseconds, remember that Snowflake reports elapsed time in milliseconds natively while many of its console views show seconds, so confirm units when reconciling. A rising p50 across an otherwise unchanged workload is the earliest sign that a warehouse is undersized, that table statistics have drifted, or that result caching has stopped serving repeat queries. Read it next to Query Latency p95 (ms) and Query Latency p99 (ms): if p50 holds steady but p95 climbs, the problem is the slow tail (a few heavy queries), whereas a rising p50 means the whole distribution has shifted and every user is feeling it. Pair with Avg Query Queue Depth per Warehouse and Slow-Query Rate % to separate “queries are slow because the warehouse is overloaded” from “queries are slow because they are badly written”. The time window is RT/1h: a live read backed by the rolling last-hour history. No alert is configured by default on the median because the action-worthy signals live in the tail percentiles.
Reconcile against the source: in a Snowflake worksheet run SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY TOTAL_ELAPSED_TIME) FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY(DATEADD('hour',-1,CURRENT_TIMESTAMP()),CURRENT_TIMESTAMP())); or open Snowsight under Monitoring to Query History and sort by duration. The Vortex IQ value should track the median over the same hour, allowing for ACCOUNT_USAGE latency.