Grafana Loki vs Quickwit
log search — label-indexed grep vs. full-text Lucene-style on object storage
| Grafana Loki | Quickwit | |
|---|---|---|
| Summary | Log aggregation inspired by Prometheus: index only labels, not full text. Cheap at scale. | Rust search engine for logs and traces with sub-second queries directly against S3-compatible object storage. |
| License | AGPL-3.0 | Apache-2.0 |
| Language | Go | Rust |
| GitHub stars (approx) | 24000 | 11000 |
| Categories | logs | logs, traces |
| Replaces SaaS | splunk, datadog, sumologic | datadog, splunk, new-relic |
| Self-host deployment | docker, kubernetes helm, single binary | single binary, docker, kubernetes helm |
| Commercial hosted option | yes (vendor-run) | no / self-host only |
| Repository | https://github.com/grafana/loki | https://github.com/quickwit-oss/quickwit |
| Freshness checked | 2026-04-22 | 2026-05-17 |
When to prefer Grafana Loki
You think of logs as labeled streams (like Prometheus metrics) and most of your queries filter by label first, then grep. Loki's index-light model is dramatically cheaper than Elasticsearch when your access patterns match it, and it integrates natively with Grafana.
When to prefer Quickwit
You need true full-text search over log content at high volume — Lucene-style queries, not regex-on-grep. Quickwit is built for indexed full-text search on object storage with a fraction of Elasticsearch's RAM footprint.