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Connect Facebook Pages to PostgreSQL

Connect Facebook Pages 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 Facebook Pages API pipeline.

Used by the world's leading companies

Export Facebook Pages data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Facebook Pages data in PostgreSQL

Bring all your Facebook Pages 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 Facebook Pages so every dashboard, model, and report works with fresh information.

Analysis

Unify Facebook Pages with the rest of your business data

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

Facebook Pages metrics and dimensions available in PostgreSQL

Access 221 metrics and 178 dimensions from Facebook Pages connectors including Fan count, Page Total Action, Post Engagement Rate, Post clicks, Page post impression, Page video views click to play, Category, Website, Page address, Verification Status, Day of the month and many more...

221

Metrics availables

178

Dimensions availables

Connect Facebook Pages to PostgreSQL in minutes

Move your data from Facebook Pages 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 Facebook Pages account

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

Client A · Connected sources
5 sources ready
Facebook Pages 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 Facebook Pages organic content performance in SQL.

This example summarizes impressions, reach, engagements, and engagement rate by post.

Facebook Pages.sql
BigQuery SQL
30-day window
SELECT
  post_id,
  SUM(impressions) AS impressions,
  SUM(reach) AS reach,
  SUM(engagements) AS engagements,
  SAFE_DIVIDE(
    SUM(engagements),
    SUM(impressions)
  ) AS engagement_rate
FROM `your_project.marketing_raw.facebook_pages_content_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY post_id
ORDER BY engagements 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.

How does a Facebook Pages-to-PostgreSQL workflow work in Catchr?

Connect Facebook Pages and add PostgreSQL as the stored destination. Create a datastream, then save a job that sends the required records to the "profiles" table.

Can I choose the Facebook Pages columns loaded into PostgreSQL?

Select concrete Facebook Pages fields such as Blue reels play count, Facebook reels replay count, Facebook reels total plays, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as accounts, profiles, and posts.

Can I choose both history and frequency for a Facebook Pages PostgreSQL job?

Choose how far back the first Facebook Pages load should go and how much recent data each "profiles" run should refresh. Catchr splits large backfills into smaller intervals.

Can Catchr refresh only the recent Facebook Pages rows in PostgreSQL?

For recurring Facebook Pages loads, assign an eligible partition field to "profiles". Otherwise Catchr cannot match the refresh window and will append the returned records.

What business questions can Facebook Pages data answer in PostgreSQL?

With Facebook Pages data, a PostgreSQL query can summarize impressions, reach, engagements, and engagement rate by post. Join Blue reels play count and Facebook reels replay count with shared account or date keys to build a reusable performance model in PostgreSQL.

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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