Grafana Bridge

chmonitor and Grafana can coexist on the same ClickHouse cluster. There is no official integration and no special bridge process — both tools query ClickHouse system tables directly using the ClickHouse HTTP or native protocol. This page explains the setup and provides copy-paste panel queries derived from the same SQL that chmonitor uses internally.

Community recipe. This is a community starting point, not an officially maintained integration. The queries are adapted from chmonitor’s query configs and target ClickHouse v23.8+. Use them as a baseline and adjust to your schema version.

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How it works

Grafana ──► ClickHouse HTTP/Native ──► system.processes
chmonitor ──► ClickHouse HTTP/Native ──► system.processes (same tables)

Both tools connect as separate clients. chmonitor uses the @clickhouse/client library; Grafana uses its ClickHouse data source plugin. Neither has any awareness of the other — they share nothing except the ClickHouse endpoint and credentials.

You can give each tool the same credentials, or create separate ClickHouse users with GRANT SELECT ON system.* (see Least-privilege connection presets).

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Install the Grafana ClickHouse data source

Install the official plugin from Grafana Labs:

grafana-cli plugins install grafana-clickhouse-datasource

Or via the Grafana UI: Configuration → Plugins → Search “ClickHouse”.

Configure the data source to point at the same ClickHouse host that chmonitor uses:

Field	Value
Server address	Your CLICKHOUSE_HOST value (without protocol)
Server port	8123 (HTTP) or 9000 (native)
Username	Same as CLICKHOUSE_USER
Password	Same as CLICKHOUSE_PASSWORD
Default database	system
TLS	Match your ClickHouse TLS settings

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Panel queries

The five queries below are adapted directly from chmonitor’s query configs. They are plain SQL — paste them into a Grafana panel’s “Query” field with the ClickHouse data source selected.

1. Running queries (system.processes)

Shows queries currently executing on the server. Equivalent to chmonitor’s Running Queries page.

SELECT
    query_id,
    user,
    elapsed,
    formatReadableTimeDelta(elapsed) AS readable_elapsed,
    read_rows,
    formatReadableQuantity(read_rows) AS readable_read_rows,
    formatReadableSize(read_bytes) AS readable_read_bytes,
    formatReadableSize(memory_usage) AS readable_memory_usage,
    length(thread_ids) AS thread_count,
    multiIf(
        interface = 1, 'TCP',
        interface = 2, 'HTTP',
        interface = 3, 'gRPC',
        interface = 4, 'MySQL',
        interface = 5, 'PostgreSQL',
        interface = 6, 'Local',
        interface = 7, 'Interserver',
        toString(interface)
    ) AS interface_label,
    substr(query, 1, 200) AS query_preview
FROM system.processes
WHERE is_cancelled = 0
ORDER BY elapsed DESC

Suggested panel type: Table. Sort by elapsed descending. Color elapsed with thresholds at 5 s (yellow) and 30 s (red).

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2. Slow queries (system.query_log)

Top slowest completed queries from the last 24 hours. Equivalent to chmonitor’s Slow Queries page.

SELECT
    query_id,
    query_start_time,
    query_duration_ms,
    query_duration_ms / 1000 AS query_duration_s,
    user,
    read_rows,
    formatReadableQuantity(read_rows) AS readable_read_rows,
    formatReadableSize(read_bytes) AS readable_read_bytes,
    formatReadableSize(memory_usage) AS readable_memory_usage,
    substr(replace(query, '\n', ' '), 1, 300) AS query_preview
FROM system.query_log
WHERE
    type = 'QueryFinish'
    AND query_duration_ms >= 5000
    AND event_time > now() - INTERVAL 24 HOUR
ORDER BY query_duration_ms DESC
LIMIT 50

Note: system.query_log must be enabled in your ClickHouse server config. The query_cache_usage column is available from ClickHouse v24.1+; omit it on older versions.

Suggested panel type: Table. Use a bar gauge overlay on query_duration_s.

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3. Active merges (system.merges)

Merges and mutations currently in progress. Equivalent to chmonitor’s Merges page.

SELECT
    database,
    table,
    partition_id,
    elapsed,
    round(progress * 100, 1) AS pct_progress,
    num_parts,
    formatReadableQuantity(rows_read) AS readable_rows_read,
    formatReadableQuantity(rows_written) AS readable_rows_written,
    formatReadableSize(memory_usage) AS readable_memory_usage,
    is_mutation,
    merge_type,
    merge_algorithm
FROM system.merges
ORDER BY progress DESC

Suggested panel type: Table. Add a stat panel with COUNT(*) for an at-a-glance merge count.

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4. Parts per table (system.parts)

Row and byte counts per active part, aggregated to the table level. Derived from chmonitor’s part-info query.

SELECT
    database,
    table,
    count() AS part_count,
    sum(rows) AS total_rows,
    formatReadableQuantity(sum(rows)) AS readable_rows,
    formatReadableSize(sum(data_compressed_bytes)) AS readable_compressed,
    formatReadableSize(sum(data_uncompressed_bytes)) AS readable_uncompressed,
    round(
        sum(data_uncompressed_bytes) / nullIf(sum(data_compressed_bytes), 0),
        2
    ) AS compression_ratio
FROM system.parts
WHERE active = 1
GROUP BY database, table
ORDER BY sum(data_compressed_bytes) DESC
LIMIT 50

Suggested panel type: Table. Highlight tables where part_count is unusually high (many small parts indicate a merge backlog).

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5. Replication lag (system.replicas)

Replication queue depth and delay per replicated table. Equivalent to chmonitor’s Replicas page.

SELECT
    database,
    table,
    engine,
    is_leader,
    is_readonly,
    absolute_delay,
    queue_size,
    inserts_in_queue,
    merges_in_queue,
    future_parts,
    total_replicas,
    active_replicas
FROM system.replicas
ORDER BY absolute_delay DESC, queue_size DESC

Note: system.replicas is only populated for tables using a Replicated*MergeTree engine. Returns empty on standalone (non-replicated) ClickHouse instances.

Suggested panel type: Table. Add a stat panel with max(absolute_delay) and a threshold alert at 60 s.

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Starter dashboard JSON

A minimal Grafana dashboard JSON is available at docs/assets/grafana/chmonitor-overview.json in this repository.

Import it via Dashboards → Import → Upload JSON file. Select your ClickHouse data source when prompted.

The starter includes all five panels above with suggested layouts and thresholds. It is a community baseline — not an official release artifact.

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Credentials and access control

chmonitor and Grafana can share a ClickHouse user or use separate users. For production, separate least-privilege users are recommended so each tool’s query traffic is identifiable in system.query_log.

Example: create a read-only Grafana user:

CREATE USER grafana_ro IDENTIFIED BY 'your-password';
GRANT SELECT ON system.* TO grafana_ro;

See Least-privilege connection presets for a complete example including network restrictions.

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Limitations

• No real-time streaming. Grafana polls ClickHouse on a configurable interval (minimum ~5 s). chmonitor’s running-queries view also polls every 5 s. Neither tool provides push-based streaming from ClickHouse.
• system.query_log retention. Slow query history depends on your query_log TTL. Default retention is 30 days; adjust via system.query_log flush_interval_milliseconds and partition TTL in your ClickHouse config.
• system.replicas requires ZooKeeper/Keeper. If your cluster does not use replication, the replicas panel returns no rows.
• ClickHouse version. Queries target v23.8+. Some columns (query_cache_usage, peak_threads_usage) are only available on newer versions — the queries fall back gracefully or note the version requirement inline.