---
title: How do I reduce ClickHouse disk size on self-hosted Langfuse?
seoTitle: "Reduce ClickHouse Disk Size When Self-Hosting"
description: "On self-hosted Langfuse, ClickHouse system log tables usually dominate disk usage. Two levers for reclaiming space, in order of recommendation."
tags: [self-hosting]
---

# How do I reduce ClickHouse disk size on self-hosted Langfuse?

On self-hosted Langfuse, disk usage is frequently dominated by ClickHouse's built-in system log tables rather than Langfuse's own tables. There are two levers, in order of recommendation:

1. **Langfuse-owned data** — configure a [data retention policy](/docs/administration/data-retention) to drop old traces, observations, scores, and their blob-storage payloads. This is the primary lever for trimming application data.
2. **ClickHouse system log tables** — by default, ClickHouse writes to `trace_log`, `text_log`, `opentelemetry_span_log`, `asynchronous_metric_log`, `metric_log`, and `latency_log` with no TTL, and runs the query profiler continuously. Langfuse does not read from these, so you can either opt out of the unused ones or attach aggressive TTLs. See [ClickHouse system log tables](/self-hosting/configuration/scaling#clickhouse-system-log-tables) in the scaling docs for concrete `config.d` snippets.

Use this query inside ClickHouse to identify the largest tables:

```sql
SELECT table, formatReadableSize(size) as size, rows FROM (
    SELECT
        table,
        database,
        sum(bytes) AS size,
        sum(rows) AS rows
    FROM system.parts
    WHERE active
    GROUP BY table, database
    ORDER BY size DESC
)
```

Related: [langfuse/langfuse#13123](https://github.com/langfuse/langfuse/issues/13123), [langfuse-terraform-aws#26](https://github.com/langfuse/langfuse-terraform-aws/pull/26).

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### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
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