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Connect Pardot to PostgreSQL

Connect Pardot 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 Pardot API pipeline.

Pardot export job

First sync scheduled

Pardot Selected accounts

Configured job

PostgreSQL Destination table

Account Pardot · Client group A

Table daily_dump

Initial import Configured historical window

Schedule Daily · 06:00 UTC

Fields Selected metrics + dimensions

Partition date · eligible field

Illustrative job · configure values for your account Export ready

Used by the world's leading companies

Export Pardot data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Pardot data in PostgreSQL

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

Source

Pardot CRM data

INaccounts PMcontacts CUcompanies BLleads

Catchr pipeline IN PM CU Extract · normalize · load

PostgreSQL catchr_data.Pardot_raw

TableScopeStatus

accountsSelectedReady

contactsSelectedReady

companiesSelectedReady

leadsSelectedReady

Data freshness

Keep your PostgreSQL tables up to date

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

PardotConfigured account

PostgreSQLPardot Metrics_raw

Rows processed Scheduled loads Example 24h

00:0006:0012:0018:00

Latest run Completed 06:00 UTC

New rows +428 4 tables updated

Next run Scheduled 12:00 UTC

accounts326 updated contacts102 appended Warehouse up to date

Analysis

Unify Pardot with the rest of your business data

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

Business data model

model / business_360

Warehouse inputs

QuickBooks accounts · Bounce Rate CRM

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

PostgreSQL model business_360 Unified

FieldFrom

customer_idCRM

Bounce Rateaccounts

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

Pardot metrics and dimensions available in PostgreSQL

Access 19 metrics and 135 dimensions from Pardot connectors including Open Rate, Click Through Rate, Click To Open Rate, Delivered, Unsubscribe Rate, Date, Campaign Name, Prospect Source, Prospect Medium, Visitor Page View URL and many more...

Metrics availables

135

Dimensions availables

View all Pardot Metrics metrics and dimensions

Connect Pardot to PostgreSQL in minutes

Move your data from Pardot 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 Pardot account

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

Connect now

Client A · Connected sources

5 sources ready

Pardot 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 Pardot sales pipeline performance in SQL.

This example summarizes pipeline value, created deals, won deals, and win rate by owner.

30-day window

SELECT
  owner_name,
  SUM(deal_value) AS deal_value,
  SUM(deals_created) AS deals_created,
  SUM(deals_won) AS deals_won,
  SAFE_DIVIDE(
    SUM(deals_won),
    SUM(deals_created)
  ) AS win_rate
FROM `your_project.marketing_raw.pardot_deals`
WHERE created_date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY owner_name
ORDER BY deal_value 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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Finance

Before you schedule the job.

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

Can Catchr send Pardot records directly to PostgreSQL?

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

How much control do I have over Pardot fields in PostgreSQL?

Select concrete Pardot fields such as Bounce Rate, Bounces, Click Through Rate, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as accounts, contacts, and companies.

How should I configure recurring Pardot imports in PostgreSQL?

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

How do I prevent duplicate Pardot rows in PostgreSQL?

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

How can a team use Pardot data after it reaches PostgreSQL?

With Pardot data, a PostgreSQL query can summarize pipeline value, created deals, won deals, and win rate by owner. Model Bounce Rate and Bounces 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 ?

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100+ sources

Used by the world's leading companies

Export Pardot data to PostgreSQL

Centralize Pardot data in PostgreSQL

Keep your PostgreSQL tables up to date

Unify Pardot with the rest of your business data

Pardot metrics and dimensions available in PostgreSQL

Connect Pardot to PostgreSQL in minutes

Connect your Pardot account

Choose the PostgreSQL destination

Keep your PostgreSQL tables updated

Review 30-day Pardot sales pipeline performance in SQL.

Choose what to load into PostgreSQL.

QuickBooks

MailerLite

JSON / CSV / XML

Firebase Realtime Database

ChatGPT

Braze

StackAdapt

Amazon DSP

AdsWizz

TikTok Shop

The Trade Desk

Outbrain DSP

Google Display & Video 360

Tiktok GMV

Chartmogul

Profitwell

Zoho CRM

Line Ads

Yahoo! Japan Display

Yahoo! Japan search ads

Xandr

Branch

Google Trends

Google Page Speed

Airbnb Review

Capterra Review

Facebook Review

Yelp Review

Glassdoor Review

Booking Review

Google Play Review

g2 Review

Appstore Review

Tripadvisor Review

Trustpilot Review

Indeed Review

Taboola

Teads

Outbrain

Magento

Prestashop

Bigcommerce

Youtube Analytics

Google Ads

Facebook Ads

LinkedIn Ads

Microsoft Ads

Facebook Pages

Amazon Ads

Pinterest Ads

X / Twitter Ads

TikTok Ads

Google Merchant Center

Google Analytics

Instagram

TikTok

Shopify

Google My Business

Snapchat Ads

LinkedIn Pages

Google Search Console

Spotify Ads

WooCommerce

Matomo

Klaviyo

Mailchimp

Pipedrive

ActiveCampaign