Tools like Metabase and Grafana are great for dashboards, but log exploration is a different workflow.
The Grafana ClickHouse plugin requires manual column configuration for logs, has no field sidebar, and its ad-hoc filters are slow on large tables. Grafana's RBAC is Enterprise-only, and even then it's datasource-level and not at table-level. If someone has access to the ClickHouse datasource, they can query any table. In Logchef, you create Sources (pointing to specific tables) and assign them to Teams. Team A only sees their logs, Team B only theirs. Fine-grained access control without any Enterprise license :)
Metabase has no concept of log-specific features at all. We kept falling back to raw SQL in clickhouse-client, which works but isn't something you want to hand to your whole team.
So I built Logchef — a log viewer designed specifically for ClickHouse. Schema-agnostic, so you can start filtering immediately without migrations.
What it does:
- Point at any ClickHouse table – no schema migrations/no OTEL requirement - LogchefQL query language (simpler than SQL for filtering) - Field sidebar like Kibana – click values to add filters - SQL-based alerting that routes to Alertmanager - AI assistant that turns natural language queries like "find slow POST requests" into working SQL - MCP server for querying logs from your favourite LLM assistant tool - Single Go binary (~15MB), embeds the frontend
We've been running this in production for 8 months and I'm excited to ship v1.0 today.
Demo: https://demo.logchef.app
GitHub: https://github.com/mr-karan/logchef
Docs: https://logchef.app
Happy to answer questions about ClickHouse for logs, the architecture, or anything else.
