> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart for Managed Postgres

> Experience NVMe-powered Postgres performance and add real-time analytics with native ClickHouse integration

This page covers provisioning ClickHouse Managed Postgres, loading data, replicating it to ClickHouse, and querying it, all from the command line with the [ClickHouse CLI](/docs/products/cloud/features/cli) (`clickhousectl`) and `psql`. Commands are non-interactive; `clickhousectl` emits JSON with `--json`.

<h2 id="prerequisites">
  Prerequisites
</h2>

Install the ClickHouse CLI:

```bash theme={null}
curl https://clickhouse.com/cli | sh
```

You also need `psql` (PostgreSQL client tools; on macOS, `brew install libpq`) and `jq`.

Write operations (create, delete) require [API key authentication](/docs/products/cloud/features/admin-features/api/openapi); OAuth login is read-only:

```bash theme={null}
clickhousectl cloud auth login --api-key <YOUR_KEY> --api-secret <YOUR_SECRET>
```

Alternatively, set the `CLICKHOUSE_CLOUD_API_KEY` and `CLICKHOUSE_CLOUD_API_SECRET` environment variables. Verify with `clickhousectl cloud auth status`; expect an entry with scope `read/write`.

<h2 id="part-1-create-and-load">
  Part 1: Create Postgres and load data
</h2>

<h3 id="create-postgres-service">
  Create a Postgres service
</h3>

Create the service and save the response; the password is shown only once:

```bash theme={null}
clickhousectl cloud postgres create \
  --name quickstart-pg \
  --region us-east-1 \
  --size c6gd.large \
  --pg-version 18 \
  --json > pg.json
```

The response includes the service ID, hostname, and a ready-to-use connection string:

```json theme={null}
{
  "id": "3b5a3112-bf02-82d0-bd02-fbe67d5caa7a",
  "name": "quickstart-pg",
  "provider": "aws",
  "region": "us-east-1",
  "postgresVersion": "18",
  "size": "c6gd.large",
  "storageSize": 118,
  "haType": "none",
  "state": "creating",
  "createdAt": "2026-07-22T13:21:22Z",
  "hostname": "quickstart-pg-c1406b50.pg7dd324nz0a1qm1fqskxbjn7m.c0.us-east-1.aws.pg.clickhouse.cloud",
  "username": "postgres",
  "password": "vV6cfEr2p_-TzkCDrZOx",
  "connectionString": "postgres://postgres:vV6cfEr2p_-TzkCDrZOx@quickstart-pg-c1406b50.pg7dd324nz0a1qm1fqskxbjn7m.c0.us-east-1.aws.pg.clickhouse.cloud:5432/postgres?channel_binding=require",
  "isPrimary": true,
  "tags": []
}
```

Extract what the rest of this guide needs:

```bash theme={null}
PG_ID=$(jq -r .id pg.json)
PG_URL=$(jq -r .connectionString pg.json)
```

If the password is lost, generate a new one with `clickhousectl cloud postgres reset-password $PG_ID --generate`.

<h3 id="wait-for-provisioning">
  Wait for the service to provision
</h3>

Provisioning takes a few minutes. Poll until the state is `running`:

```bash theme={null}
while [ "$(clickhousectl cloud postgres get "$PG_ID" --json | jq -r .state)" != "running" ]; do
  sleep 15
done
```

<h3 id="load-sample-data">
  Load sample data
</h3>

Create two tables and insert 1 million events over `psql`:

```bash theme={null}
psql "$PG_URL" <<'SQL'
\timing
CREATE TABLE events (
   event_id SERIAL PRIMARY KEY,
   event_name VARCHAR(255) NOT NULL,
   event_type VARCHAR(100),
   event_timestamp TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
   event_data JSONB,
   user_id INT,
   user_ip INET,
   is_active BOOLEAN DEFAULT TRUE,
   created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
   updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);

CREATE TABLE users (
   user_id SERIAL PRIMARY KEY,
   name VARCHAR(100),
   country VARCHAR(50),
   platform VARCHAR(50)
);

INSERT INTO events (event_name, event_type, event_timestamp, event_data, user_id, user_ip)
SELECT
   'Event ' || gs::text AS event_name,
   CASE
       WHEN random() < 0.5 THEN 'click'
       WHEN random() < 0.75 THEN 'view'
       WHEN random() < 0.9 THEN 'purchase'
       WHEN random() < 0.98 THEN 'signup'
       ELSE 'logout'
   END AS event_type,
   NOW() - INTERVAL '1 day' * (gs % 365) AS event_timestamp,
   jsonb_build_object('key', 'value' || gs::text, 'additional_info', 'info_' || (gs % 100)::text) AS event_data,
   GREATEST(1, LEAST(1000, FLOOR(POWER(random(), 2) * 1000) + 1)) AS user_id,
   ('192.168.1.' || ((gs % 254) + 1))::inet AS user_ip
FROM
   generate_series(1, 1000000) gs;

INSERT INTO users (name, country, platform)
SELECT
    first_names[first_idx] || ' ' || last_names[last_idx] AS name,
    CASE
        WHEN random() < 0.25 THEN 'India'
        WHEN random() < 0.5 THEN 'USA'
        WHEN random() < 0.7 THEN 'Germany'
        WHEN random() < 0.85 THEN 'China'
        ELSE 'Other'
    END AS country,
    CASE
        WHEN random() < 0.2 THEN 'iOS'
        WHEN random() < 0.4 THEN 'Android'
        WHEN random() < 0.6 THEN 'Web'
        WHEN random() < 0.75 THEN 'Windows'
        WHEN random() < 0.9 THEN 'MacOS'
        ELSE 'Linux'
    END AS platform
FROM
    generate_series(1, 1000) AS seq
    CROSS JOIN LATERAL (
        SELECT
            array['Alice', 'Bob', 'Charlie', 'Diana', 'Eve', 'Frank', 'Grace', 'Hank', 'Ivy', 'Jack', 'Liam', 'Olivia', 'Noah', 'Emma', 'Sophia', 'Benjamin', 'Isabella', 'Lucas', 'Mia', 'Amelia', 'Aarav', 'Riya', 'Arjun', 'Ananya', 'Wei', 'Li', 'Huan', 'Mei', 'Hans', 'Klaus', 'Greta', 'Sofia'] AS first_names,
            array['Smith', 'Johnson', 'Williams', 'Brown', 'Jones', 'Garcia', 'Miller', 'Davis', 'Martinez', 'Taylor', 'Anderson', 'Thomas', 'Jackson', 'White', 'Harris', 'Martin', 'Thompson', 'Moore', 'Lee', 'Perez', 'Sharma', 'Patel', 'Gupta', 'Reddy', 'Zhang', 'Wang', 'Chen', 'Liu', 'Schmidt', 'Müller', 'Weber', 'Fischer'] AS last_names,
            1 + (seq % 32) AS first_idx,
            1 + ((seq / 32)::int % 32) AS last_idx
    ) AS names;
SQL
```

```text theme={null}
Timing is on.
CREATE TABLE
Time: 86.029 ms
CREATE TABLE
Time: 80.962 ms
INSERT 0 1000000
Time: 7120.357 ms (00:07.120)
INSERT 0 1000
Time: 84.807 ms
```

The 1M-row insert completes in about 7 seconds on `c6gd.large` (the smallest size) thanks to NVMe storage. Verify with a query; row counts vary between runs because the data is generated with `random()`:

```bash theme={null}
psql "$PG_URL" -c "SELECT event_type, COUNT(*) FROM events GROUP BY event_type ORDER BY 2 DESC;"
```

<h2 id="part-2-replicate">
  Part 2: Replicate to ClickHouse
</h2>

<h3 id="create-clickhouse-service">
  Create a ClickHouse service
</h3>

Create a service in the same region and save the response; the password appears only in the create response:

```bash theme={null}
clickhousectl cloud service create \
  --name quickstart-ch \
  --region us-east-1 \
  --json > ch.json

CH_ID=$(jq -r .service.id ch.json)
CH_PASSWORD=$(jq -r .password ch.json)
```

Wait until it's running; the ClickPipe requires a running destination:

```bash theme={null}
while [ "$(clickhousectl cloud service get "$CH_ID" --json | jq -r .state)" != "running" ]; do
  sleep 15
done
```

To use an existing service instead, set `CH_ID` from `clickhousectl cloud service list` and `CH_PASSWORD` to its `default` user password, which the `pg_clickhouse` step needs.

<h3 id="replicate-to-clickhouse">
  Replicate the tables to ClickHouse
</h3>

Create a Postgres CDC ClickPipe on the ClickHouse service, pointing at the Managed Postgres hostname. The pipe copies the existing rows, then keeps ClickHouse in sync with ongoing changes:

```bash theme={null}
PG_HOST=$(jq -r .hostname pg.json)
PG_PASSWORD=$(jq -r .password pg.json)

clickhousectl cloud clickpipe create postgres "$CH_ID" \
  --name quickstart-sync \
  --host "$PG_HOST" \
  --pg-database postgres \
  --username postgres \
  --password "$PG_PASSWORD" \
  --table-mapping public.events:public_events \
  --table-mapping public.users:public_users \
  --json > pipe.json

PIPE_ID=$(jq -r .id pipe.json)
```

Notes:

* The replicated tables land in the `default` database on the ClickHouse service, named by the `--table-mapping` targets
* The publication and replication slot are created automatically, with the publication scoped to the mapped tables; pass `--publication-name` to use one you manage yourself
* Use the direct Postgres hostname; replication isn't supported via PgBouncer

<h3 id="wait-for-pipe">
  Wait for the pipe to reach Running
</h3>

The pipe moves through `Provisioning`, `Setup`, and (for larger tables) `Snapshot` before reaching `Running`, which takes about 4 minutes for the first pipe on a service. `Failed` and `InternalError` are terminal:

```bash theme={null}
while :; do
  STATE=$(clickhousectl cloud clickpipe get "$CH_ID" "$PIPE_ID" --json | jq -r .state)
  case "$STATE" in
    Running) break ;;
    Failed|InternalError) echo "ClickPipe entered terminal state: $STATE" >&2; exit 1 ;;
  esac
  sleep 15
done
```

<h3 id="query-clickhouse">
  Query the replicated data in ClickHouse
</h3>

Run SQL against the ClickHouse service directly from the CLI. The first call provisions a Query API endpoint and a service-scoped API key automatically:

```bash theme={null}
clickhousectl cloud service query --id "$CH_ID" \
  --query "SELECT count() FROM public_events"
```

```text theme={null}
Provisioning Query API endpoint + key for service 'quickstart-ch'...
1000000
```

New writes to Postgres replicate continuously. Insert a row and poll until the count reaches 1,000,001 (typically under a minute):

```bash theme={null}
psql "$PG_URL" -c "INSERT INTO events (event_name, event_type, user_id, user_ip) VALUES ('cdc-test', 'click', 42, '10.0.0.1');"

while [ "$(clickhousectl cloud service query --id "$CH_ID" \
  --query "SELECT count() FROM public_events")" != "1000001" ]; do
  sleep 10
done
```

<h3 id="query-clickhouse-from-postgres">
  Query ClickHouse from Postgres
</h3>

The [`pg_clickhouse`](/docs/products/managed-postgres/extensions/pg_clickhouse/introduction) extension lets Postgres act as a unified query layer for both transactional and analytical data. Grab the ClickHouse HTTPS hostname, then set up the extension over `psql`:

```bash theme={null}
CH_HOST=$(clickhousectl cloud service get "$CH_ID" --json \
  | jq -r '.endpoints[] | select(.protocol=="https") | .host')

psql "$PG_URL" <<SQL
CREATE EXTENSION pg_clickhouse;
CREATE SERVER ch FOREIGN DATA WRAPPER clickhouse_fdw
       OPTIONS(driver 'http', host '$CH_HOST', dbname 'default', port '8443');
CREATE USER MAPPING FOR CURRENT_USER SERVER ch
       OPTIONS (user 'default', password '$CH_PASSWORD');
CREATE SCHEMA organization;
IMPORT FOREIGN SCHEMA "default" FROM SERVER ch INTO organization;
SQL
```

The heredoc is unquoted on purpose, so the shell substitutes `$CH_HOST` and `$CH_PASSWORD` before the SQL reaches Postgres. The replicated tables are now visible as foreign tables in the `organization` schema; queries against them execute in ClickHouse.

Measured on `c6gd.large` with this dataset, analytical queries run 6-9x faster through the foreign tables (for example, a 5-aggregation GROUP BY: 176 ms via ClickHouse vs 1,133 ms locally; a JOIN with aggregations: 298 ms vs 2,764 ms).

<h2 id="cleanup-resources">
  Cleanup
</h2>

Delete the ClickPipe first, then the Postgres service. Deleting a service removes all of its data permanently:

```bash theme={null}
clickhousectl cloud clickpipe delete "$CH_ID" "$PIPE_ID"
clickhousectl cloud postgres delete "$PG_ID"
```

A running ClickHouse service can't be deleted directly. Stop it, wait for `stopped`, then delete:

```bash theme={null}
clickhousectl cloud service stop "$CH_ID"

while [ "$(clickhousectl cloud service get "$CH_ID" --json | jq -r .state)" != "stopped" ]; do
  sleep 10
done

clickhousectl cloud service delete "$CH_ID"
```