This integration is powered by Singer's Autopilot tap. For support, visit the GitHub repo or join the Singer Slack.
Autopilot integration summary
Autopilot feature snapshot
A high-level look at Stitch's Autopilot (v1.0) integration, including release status, useful links, and the features supported in Stitch.
|Release Status||Released||Supported By|
|Singer GitHub Repository|
|Configurable Replication Methods||
Step 1: Retrieve your Autopilot API Key
- Sign into your Autopilot account.
- Click the gear (Settings) icon on the left side of the page.
- In the Settings menu, click Autopilot API.
- If you haven’t used the API before, you’ll need to generate a new key. Click the Generate button.
- Your API Key will display.
Make sure you keep this key safe, as it has access to your Autopilot account. If at any time your key is lost or compromised, you can click the Regenerate button to generate a new key. Remember to also update the key in Stitch or you’ll encounter connection issues.
Step 2: Add Autopilot as a Stitch data source
- Sign into your Stitch account.
On the Stitch Dashboard page, click the Add Integration button.
Click the Autopilot icon.
Enter a name for the integration. This is the name that will display on the Stitch Dashboard for the integration; it’ll also be used to create the schema in your destination.
For example, the name “Stitch Autopilot” would create a schema called
stitch_autopilotin the destination. Note: Schema names cannot be changed after you save the integration.
Step 3: Define the historical sync
The Sync Historical Data setting will define the starting date for your Autopilot integration. This means that:
- For tables using Incremental Replication, data equal to or newer than this date will be replicated to your data warehouse.
- For tables using Full Table Replication, all data - including records that are older, equal to, or newer than this date - will be replicated to your data warehouse.
Change this setting if you want to replicate data beyond Autopilot’s default setting of 1 year. For a detailed look at historical replication jobs, check out the Syncing Historical SaaS Data guide.
Step 4: Create a replication schedule
In the Replication Frequency section, you’ll create the integration’s replication schedule. An integration’s replication schedule determines how often Stitch runs a replication job, and the time that job begins.
Autopilot integrations support the following replication scheduling methods:
To keep your row usage low, consider setting the integration to replicate less frequently. See the Understanding and Reducing Your Row Usage guide for tips on reducing your usage.
Initial and historical replication jobs
After you finish setting up Autopilot, its Sync Status may show as Pending on either the Stitch Dashboard or in the Integration Details page.
For a new integration, a Pending status indicates that Stitch is in the process of scheduling the initial replication job for the integration. This may take some time to complete.
Initial replication jobs with Anchor Scheduling
If using Anchor Scheduling, an initial replication job may not kick off immediately. This depends on the selected Replication Frequency and Anchor Time. Refer to the Anchor Scheduling documentation for more information.
Free historical data loads
The first seven days of replication, beginning when data is first replicated, are free. Rows replicated from the new integration during this time won’t count towards your quota. Stitch offers this as a way of testing new integrations, measuring usage, and ensuring historical data volumes don’t quickly consume your quota.
Autopilot table schemas
Schemas and versioning
Schemas and naming conventions can change from version to version, so we recommend verifying your integration’s version before continuing.
The schema and info displayed below is for version 1.0 of this integration.
This is the latest version of the Autopilot integration.
Table and column names in your destination
Depending on your destination, table and column names may not appear as they are outlined below.
For example: Object names are lowercased in Redshift (
customers), while case is maintained in PostgreSQL destinations (
CusTomERs). Refer to the Loading Guide for your destination for more info.