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

# Quick Start

> Build and run a real PostgreSQL-to-PostgreSQL pipeline in the current MantrixFlow workspace.

This quick start follows the live app flow.

**Scenario:** a team wants to copy `public.orders` from an application PostgreSQL database into `analytics.orders_live` in a reporting PostgreSQL database.

## Before you begin

Have these ready:

* PostgreSQL source host, port, database, username, password, and SSL mode
* PostgreSQL destination host, port, database, username, password, and SSL mode
* A source user with read access to `public.orders`
* A destination user with write access to `analytics.orders_live`
* A pre-created destination table named `analytics.orders_live`

Example destination shape:

```sql theme={"theme":{"light":"github-light","dark":"github-dark"}}
CREATE SCHEMA IF NOT EXISTS analytics;

CREATE TABLE IF NOT EXISTS analytics.orders_live (
  id bigint PRIMARY KEY,
  customer_id bigint,
  order_status text,
  total_amount numeric,
  created_at timestamptz,
  updated_at timestamptz
);
```

## Build the pipeline

1. Open **Connections** and create a **Source** connection with **PostgreSQL**.
2. Fill the connection form and click **Test Connection**.
3. Save the source after the test succeeds.
4. Create a second **PostgreSQL** connection with the role set to **Destination**.
5. Click **Test Connection** and save the destination after the test succeeds.
6. Open **Data Pipelines** and create a new pipeline with a name and the source connection.
7. In the builder, click the settings icon on the **Source** node.
8. Click **Discover schema** or **Refresh tables**.
9. Include `public.orders` and preview the rows.
10. Click the settings icon on the **Destination** node.
11. Choose the destination connection.
12. Keep **Sync mode** as `FULL_TABLE` for the first validation run.
13. Keep **Write mode** as `Upsert`.
14. In the **SQL Layer** tab, set the final delivery table to `analytics.orders_live`.
15. Use a simple SQL model:

```sql theme={"theme":{"light":"github-light","dark":"github-dark"}}
SELECT
  id,
  customer_id,
  LOWER(order_status) AS order_status,
  total_amount,
  created_at,
  updated_at
FROM {{ source('raw', 'public__orders') }}
WHERE order_status IS NOT NULL
```

16. Click **Validate SQL**.
17. Click **Preview output**.
18. Click **Save destination**.
19. Run the destination manually from the destination node.
20. Open run status or run history and confirm the run succeeded.

## Add a schedule later

Scheduling is available after switching the destination to `INCREMENTAL` and providing a replication key such as `updated_at`.

Validate at least one manual run before enabling a recurring schedule.