Outbrain (v2) | Stitch Documentation

Outbrain is supported by the Singer community
This integration is powered by Singer's Outbrain tap. For support, visit the GitHub repo or join the Singer Slack.

Outbrain integration summary

Stitch’s Outbrain integration replicates data using the Outbrain Amplify API v2. Refer to the Schema section for a list of objects available for replication.

Outbrain feature snapshot

A high-level look at Stitch's Outbrain (v2) integration, including release status, useful links, and the features supported in Stitch.

STITCH
Release status	Released on February 11, 2026	Supported by	Singer Community
Stitch plan	Standard	API availability	Available
Singer GitHub repository	singer-io/tap-outbrain
REPLICATION SETTINGS
Anchor Scheduling	Supported	Advanced Scheduling	Supported
Table-level reset	Unsupported	Configurable Replication Methods	Unsupported
DATA SELECTION
Table selection	Supported	Column selection	Unsupported
Select all	Supported
TRANSPARENCY
Extraction Logs	Supported	Loading Reports	Supported

Connecting Outbrain

Step 1: Add Outbrain as a Stitch data source

Sign into your Stitch account.
On the Stitch Dashboard page, click the Add Integration button.
Click the Outbrain 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 Outbrain” would create a schema called stitch_outbrain in the destination. Note: Schema names cannot be changed after you save the integration.
In the Account ID field, enter your Outbrain Account (or Marketer) ID.

You can find this by looking at the URL when you’re logged into your Outbrain account. The Account ID looks something like this: 0f4b02153ee75f3c9dc4fc128ab041962 and is located between marketers and campaigns, if you’re looking at the Overview dashboard:

https://my.outbrain.com/amplify/site/marketers/[account-id-will-be-here]/campaigns/overview
In the Username field, enter your Outbrain username.
In the Password field, enter your Outbrain password.

Step 2: Define the historical replication start date

The Sync Historical Data setting defines the starting date for your Outbrain integration. This means that data equal to or newer than this date will be replicated to your data warehouse.

Change this setting if you want to replicate data beyond Outbrain’s default setting of 1 year. For a detailed look at historical replication jobs, check out the Syncing Historical SaaS Data guide.

Step 3: Create a replication schedule

Replication schedules affect the time Extraction begins, not the time to data loaded. Refer to the Replication Scheduling documentation for more information.

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.

Outbrain integrations support the following replication scheduling methods:

Replication Frequency
Anchor Scheduling
Advanced Scheduling using Cron (Advanced or Premium plans only)

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.

Step 4: Set objects to replicate

Is an object missing or not replicating? Verify that the object meets the requirements for selection and replication.

The last step is to select the tables you want to replicate. Learn about the available tables for this integration.

Note: If a replication job is currently in progress, new selections won’t be used until the next job starts.

For Outbrain integrations, you can select:

Individual tables
All tables

Click the tabs to view instructions for each selection method.

In the integration’s Tables to Replicate tab, locate a table you want to replicate.
To track a table, click the checkbox next to the table’s name. A blue checkmark means the table is set to replicate.
Repeat this process for all the tables you want to replicate.
When finished, click the Finalize Your Selections button at the bottom of the screen to save your selections.

Important: Using the Select All feature will overwrite any previous selections. However, selections aren’t final until Finalize Your Selections is clicked. Clicking Cancel will restore your previous selections. Refer to the Select All guide for more info about this feature.

Click into the integration from the Stitch Dashboard page.
Click the Tables to Replicate tab.
In the list of tables, click the box next to the Table Names column.
In the menu that displays, click Track all Tables and Fields:
Click the Finalize Your Selections button at the bottom of the page to save your data selections.

Initial and historical replication jobs

After you finish setting up Outbrain, 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.

Replication will continue after the seven days are over. If you’re no longer interested in this source, be sure to pause or delete the integration to prevent unwanted usage.

Outbrain table reference

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 2 of this integration.

This is the latest version of the Outbrain 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 > customers), while case is maintained in PostgreSQL destinations (CusTomERs > CusTomERs). Refer to the Loading Guide for your destination for more info.

campaign

The campaign table contains info about your Outbrain campaigns.

Replication Method

Full Table

Primary Key

Useful links

Outbrain documentation

campaign schema on GitHub

Outbrain API method

campaign table schema

STRING

name

STRING

campaignOnAir

BOOLEAN

onAirReason

STRING

enabled

BOOLEAN

budget

OBJECT

Click to expand budget

STRING

name

STRING

shared

BOOLEAN

amount

NUMBER

currency

STRING

amountRemaining

NUMBER

amountSpent

NUMBER

creationTime

STRING

lastModified

STRING

startDate

STRING

endDate

STRING

runForever

BOOLEAN

type

STRING

pacing

STRING

dailyTarget

NUMBER

maximumAmount

NUMBER

cpc

NUMBER

campaign_performance

The campaign_performance table contains performance metrics for your Outbrain campaigns.

Replication Method	Key-based Incremental
Primary Keys	campaignId fromDate
Replication Key	fromDate
	The `fromDate` replication key uses timestamp (date-time) format in V2, allowing granular replication tracking.
Useful links	Outbrain documentation campaign_performance schema on GitHub Outbrain API method

campaign_performance table schema

campaignId

STRING

fromDate

STRING

impressions

NUMBER

clicks

NUMBER

ctr

NUMBER

spend

NUMBER

ecpc

NUMBER

conversions

NUMBER

conversionRate

NUMBER

cpa

NUMBER

Questions? Feedback?

Did this article help? If you have questions or feedback, feel free to submit a pull request with your suggestions, open an issue on GitHub, or reach out to us.

Related	Troubleshooting
Destination & Integration Compatibility Replication Scheduling Syncing Historical SaaS Data Resetting Replication Keys Nested Data Structures & Row Count Impact	Understanding & Reducing Your Usage Re-Authorizing Integrations Replication Issues