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Connect Outbrain to PostgreSQL

Connect Outbrain to PostgreSQL and export selected accounts, metrics, and dimensions to your PostgreSQL project.

Configure the historical window, destination table, and recurring schedule without maintaining a Outbrain API pipeline.

Used by the world's leading companies

Export Outbrain data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Outbrain data in PostgreSQL

Bring all your Outbrain data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your PostgreSQL tables up to date

Automatically sync new data from Outbrain so every dashboard, model, and report works with fresh information.

Analysis

Unify Outbrain with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Outbrain metrics and dimensions available in PostgreSQL

Access 37 metrics and 68 dimensions from Outbrain connectors including Spend, Impressions, Clicks, CTR, Conversions, CPA, ROAS, Total Conversion Value, Date, Campaign Name, Campaign ID, Promoted Content Title, Promoted Content URL, Publisher Name, Country Name, Platform and many more...

37

Metrics availables

68

Dimensions availables

Connect Outbrain to PostgreSQL in minutes

Move your data from Outbrain to PostgreSQL with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Outbrain account

Authenticate your Outbrain account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Outbrain 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the PostgreSQL destination

Add the database host and credentials once. Catchr checks the connection so your exports start with a reachable destination.

Destination / PostgreSQL Required fields
Host Required
warehouse.company.net
Username Required
catchr_writer
Password Required
••••••••••••
Database Required
marketing
Step three

Keep your PostgreSQL tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example
Schema Destination
marketing_raw
Table Per job
linkedin_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 07:00
Weekly · Mon
First sync scheduledSelected fields · configured history
07:00 UTC

Review 30-day Outbrain campaign delivery in SQL.

This example summarizes spend, impressions, clicks, and click-through rate by campaign.

Outbrain.sql
BigQuery SQL
30-day window
SELECT
  campaign_name,
  SUM(spend) AS spend,
  SUM(impressions) AS impressions,
  SUM(clicks) AS clicks,
  SAFE_DIVIDE(
    SUM(clicks),
    SUM(impressions)
  ) AS ctr
FROM `your_project.marketing_raw.outbrain_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY campaign_name
ORDER BY spend DESC;
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into PostgreSQL.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

What is the setup for sending Outbrain data to PostgreSQL?

Add Outbrain in Sources and connect the existing PostgreSQL database in Storage. A datastream defines the route, while the job loads the chosen fields into "ads".

What can I select from Outbrain before writing to PostgreSQL?

Select concrete Outbrain fields such as Apple SKAdNetwork Conversion Average Value, Apple SKAdNetwork Conversion Value, Apple SKAdNetwork Conversions, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as accounts, advertisers, and campaigns.

Can an Outbrain-to-PostgreSQL job import historical periods?

Define the first Outbrain fetch, run frequency, and lookback window in the "ads" job. Each scheduled run replaces data inside the configured period.

Why does the Outbrain PostgreSQL job need a partition field?

Use a supported date field to partition "ads". Recurring Outbrain runs can then update the selected window instead of adding another copy of the same period.

Which decisions can an Outbrain dataset in PostgreSQL support?

With Outbrain data, a PostgreSQL query can summarize spend, impressions, clicks, and click-through rate by campaign. Model Apple SKAdNetwork Conversion Average Value and Apple SKAdNetwork Conversion Value in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

Does my PostgreSQL database need to exist before I connect it?

Yes. Connect an existing PostgreSQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Postgres database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

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