# mgartner/pg_flame

A flamegraph generator for Postgres EXPLAIN ANALYZE output.

Repository: https://github.com/mgartner/pg_flame
Canonical: https://ross.abutalabs.com/products/pg_flame
Language: Go
License: Apache-2.0
License Family: permissive
Topics: flamegraph, postgres, performance, performance-visualization, postgresql, postgresql-tool, database
Last push: 2020-01-13T23:28:06+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2513, "days_push": 2424, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1620, forks 36 (observed 2026-08-28T04:05:12.283340+00:00)

## What it is
pg_flame is a command-line tool that converts Postgres EXPLAIN ANALYZE JSON output into an interactive flamegraph HTML visualization. It helps developers see where time is spent in query plan execution.

## Use cases
- visualize postgres query plan execution times as a flamegraph
- debug slow postgres queries
- turn EXPLAIN ANALYZE JSON output into a flamegraph
- find which parts of a query plan consume the most time
- profile postgres query performance

## When to choose
- you want a quick, pipeable CLI to visualize Postgres EXPLAIN ANALYZE output
- you prefer simple stdin/stdout Unix-style tooling
- you need a lightweight alternative to full query analyzers

## When to avoid
- you need a GUI query analyzer with historical tracking
- you use databases other than Postgres
- you need actively developed features or support

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: data-visualization, developer-tools
- domain: databases, performance, developer-tools
- platform: cli, windows
- tags: flamegraph, postgresql, explain-analyze, query-plans, go, linux, macos, docker

## Member repositories
- mgartner/pg_flame (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:12.283340+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:49:19.284166+00:00, confidence not recorded.
  - readme: https://github.com/mgartner/pg_flame (fetched 2026-08-28T04:05:12.283340+00:00, sha 40e641869fe0)
- Data as of 2026-08-30T08:39:29.467469+00:00.