> ## 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.

# Asana to PostgreSQL, MySQL, and Airtable

> Configure all eight Asana streams and deliver published models to PostgreSQL, MySQL, or an existing Airtable table.

This example uses one Asana source with all eight supported streams. The route
has been verified through the customer UI against PostgreSQL, MySQL, and
Airtable destinations.

## 1. Prepare connections

1. Create, test, and save an Asana source by following the
   [Asana source guide](/connections/sources/productivity/asana).
2. Create and test any destination connections you need:
   * PostgreSQL
   * MySQL
   * Airtable

For Airtable, prepare an existing base and table. Runtime delivery does not
create Airtable tables.

## 2. Configure the Asana Source tab

1. Create a pipeline with the saved Asana connection.
2. Open **Source** and run discovery.
3. Select one workspace and the required projects.
4. Save the Asana scope.
5. Select `workspaces`, `projects`, `sections`, `tags`, `tasks`, `stories`,
   `teams`, and `users`.
6. Use Full Table for all streams in the first run.
7. Preview each stream and save stream settings.

<Warning>
  Keep tasks in Full Table mode when stories are selected. Stories require the
  complete task dependency traversal.
</Warning>

## 3. Add destinations

Open **Destinations** and add each saved destination connection. You can test
all three routes in one pipeline or use a separate pipeline per destination.

Suggested destination names:

* `Asana → PostgreSQL`
* `Asana → MySQL`
* `Asana → Airtable`

## 4. Publish eight transformations per destination

Create one destination-owned transformation for every Asana stream. Start with
an explicit projection and use `gid` as the stable output key.

Example tasks model:

```sql theme={"theme":{"light":"github-light","dark":"github-dark"}}
SELECT
  gid,
  name,
  completed,
  assignee__gid AS assignee_gid,
  due_on,
  modified_at
FROM {{ source('raw', 'asana__tasks') }}
```

For every transformation:

1. Save the draft.
2. Validate it.
3. Preview the output.
4. Publish the revision.

Only published revisions run.

## 5. Configure PostgreSQL and MySQL targets

Use one table per stream. Example contracts:

| Stream     | PostgreSQL                         | MySQL                              | Upsert key |
| ---------- | ---------------------------------- | ---------------------------------- | ---------- |
| Workspaces | `public.postgres_asana_workspaces` | `defaultdb.mysql_asana_workspaces` | `gid`      |
| Projects   | `public.postgres_asana_projects`   | `defaultdb.mysql_asana_projects`   | `gid`      |
| Sections   | `public.postgres_asana_sections`   | `defaultdb.mysql_asana_sections`   | `gid`      |
| Tags       | `public.postgres_asana_tags`       | `defaultdb.mysql_asana_tags`       | `gid`      |
| Tasks      | `public.postgres_asana_tasks`      | `defaultdb.mysql_asana_tasks`      | `gid`      |
| Stories    | `public.postgres_asana_stories`    | `defaultdb.mysql_asana_stories`    | `gid`      |
| Teams      | `public.postgres_asana_teams`      | `defaultdb.mysql_asana_teams`      | `gid`      |
| Users      | `public.postgres_asana_users`      | `defaultdb.mysql_asana_users`      | `gid`      |

Use **Create or verify destination table** before the first run. This explicit
setup action may add newly discovered flattened columns. Runtime delivery only
writes to the configured tables; it does not create surprise tables.

## 6. Configure the Airtable target

Select an existing Airtable base and table. Map the Asana `gid` output column
to a writable Airtable field, usually the primary `Name` field in a dedicated
test table, and select that field as the merge key.

The current Airtable destination assigns one selected table to the destination.
If all eight transformations share it, their records share that table. Use
separate Airtable destinations or tables when each stream needs an independent
business schema.

## 7. Validate and run

1. Open **Overview** and click **Validate pipeline**.
2. Resolve every missing published revision, destination table, or merge key.
3. Click **Run all**, or use a destination's **Run** action to test one target.
4. Open **Runs** and confirm the latest row for each destination is successful.
5. Verify direct counts in PostgreSQL, MySQL, or Airtable.

Source data can change between destination runs, so small differences in row
counts are normal. A successful run must report zero failed rows and its direct
destination counts must match that run's delivered output.

## 8. Move tasks to Incremental

After a successful Full Table baseline, tasks can use Incremental mode with:

* cursor: `modified_at`
* merge key: `gid`
* optional initial sync start: ISO timestamp saved in Asana extraction scope

Do not select stories in the same run when tasks are incremental. Schedule a
periodic Full Table reconciliation for project membership changes that do not
advance Asana's task `modified_at` value.