# Prometheus vs Grafana: source lines of code compared

The Prometheus vs Grafana comparison on OctoCounts shows side-by-side source line counts for prometheus/prometheus and grafana/grafana, counted with the same engine and analysis options on the dates shown in the methodology line: files, total lines, code lines, comment lines, blank lines, and per-language totals, pinned to the exact commits listed below.

As of 2026-09-16, prometheus/prometheus contains 543,787 total lines (453,215 code) across 1,439 files, while grafana/grafana contains 4,445,772 total lines (3,824,008 code) across 20,552 files as of 2026-09-20. grafana/grafana is about 8.4x the size of prometheus/prometheus by code lines. Code size is not code quality: a larger count only means more source material, not a better or worse project.

| Metric | [prometheus/prometheus](https://octocounts.com/github/prometheus/prometheus) | [grafana/grafana](https://octocounts.com/github/grafana/grafana) |
| --- | ---: | ---: |
| Files | 1,439 | 20,552 |
| Total lines | 543,787 | 4,445,772 |
| Code lines | 453,215 | 3,824,008 |
| Comment lines | 46,661 | 240,506 |
| Blank lines | 43,911 | 381,258 |
| Languages counted | 12 | 12 |

Top languages in prometheus/prometheus: Go (67.7% of code), YAML (16.0% of code), JSON (6.0% of code). Top languages in grafana/grafana: JSON (33.8% of code), Go (31.1% of code), TypeScript (16.3% of code). Go, JSON, TSX, TypeScript appear in both top language lists; YAML appears only in prometheus/prometheus's top languages; SVG appears only in grafana/grafana's top languages.

Methodology: both counts come from cached OctoCounts reports generated with tokei. prometheus/prometheus was counted at ref 3fab29b0da5f31f98893b73bcc2b20fcf79d0e1e (commit 3fab29b0da5f) on 2026-09-16; grafana/grafana was counted at ref main (commit 39703a2c01e3) on 2026-09-20. See the [counting methodology](https://octocounts.com/docs/methodology) for ignored directories and analysis options.
## About this comparison

prometheus/prometheus counts the Prometheus monitoring server: scraping, the TSDB storage engine, the PromQL query engine, alerting, and web UI — a single-repository Go server. grafana/grafana counts the Grafana observability platform: a Go backend plus a TypeScript frontend with its plugin system. The comparison is therefore a backend-only server against a full-stack application, counted with the same engine on the dates above.

Prometheus's counted tree is predominantly Go because the entire server — including its own time-series database and query engine — lives in one repository; Grafana's per-language table shows the Go/TypeScript split of a platform that delegates storage to external datasources instead of embedding one.

Both trees include operational material beyond core code — Grafana its bundled plugins and provisioning, Prometheus its web UI and extensive rule/test fixtures — so part of each count is surface area for operators and extension authors.

_The totals describe different scopes of responsibility: Prometheus ships its storage engine in-repo while Grafana connects to storage elsewhere. A larger or smaller count here does not map to capability, and neither number measures the resource cost of running either system._

Sources: [prometheus/prometheus repository (server, TSDB, and query engine)](https://github.com/prometheus/prometheus) · [grafana/grafana repository](https://github.com/grafana/grafana). Statements verified 2026-09-16.

Evidence and next steps:

- [prometheus/prometheus SLOC report](https://octocounts.com/github/prometheus/prometheus)
- [grafana/grafana SLOC report](https://octocounts.com/github/grafana/grafana)
- [Compare prometheus/prometheus and grafana/grafana interactively](https://octocounts.com/compare?left=https%3A%2F%2Fgithub.com%2Fprometheus%2Fprometheus&right=https%3A%2F%2Fgithub.com%2Fgrafana%2Fgrafana)

Note: code size is not code quality. OctoCounts only reports reproducible line counts and makes no claim that either project is better.

## Compare FAQ

### Which has more lines of code, prometheus/prometheus or grafana/grafana?

grafana/grafana has more code: 3,824,008 code lines versus 453,215 for prometheus/prometheus, about 8.4x as much, based on cached OctoCounts reports as of 2026-09-20.

### Does more source lines of code mean more complexity?

Not necessarily. SLOC measures size, not complexity, quality, or maintainability. A larger codebase can mean more features, more generated or vendored code, more verbose language idioms, or more tests — none of which imply the code is harder to work with. Use SLOC to gauge the scale of what you'd be reading or maintaining, not as a quality signal for prometheus/prometheus, grafana/grafana, or any repository.

### How is this comparison calculated?

Methodology: both counts come from cached OctoCounts reports generated with tokei. prometheus/prometheus was counted at ref 3fab29b0da5f31f98893b73bcc2b20fcf79d0e1e (commit 3fab29b0da5f) on 2026-09-16; grafana/grafana was counted at ref main (commit 39703a2c01e3) on 2026-09-20. See the counting methodology for ignored directories and analysis options.

### Can I compare a different branch, tag, or commit?

Yes. This page shows the default branch for each repository. Use the interactive comparison tool to pick any public GitHub repository, branch, tag, or commit SHA for both sides and get a fresh side-by-side report.

## Related OctoCounts pages

- [Interactive repository comparison](https://octocounts.com/compare)
- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [OctoCounts API docs](https://octocounts.com/docs/api)