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Connect Amazon DSP to PostgreSQL

Connect Amazon DSP 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 Amazon DSP API pipeline.

Used by the world's leading companies

Export Amazon DSP data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Amazon DSP data in PostgreSQL

Bring all your Amazon DSP 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 Amazon DSP so every dashboard, model, and report works with fresh information.

Analysis

Unify Amazon DSP with the rest of your business data

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

Amazon DSP metrics and dimensions available in PostgreSQL

Access 448 metrics and 94 dimensions from Amazon DSP connectors including Total ROAS, Combined Product Sales, Purchases, New To Brand Purchases, E CPC, Amazon Date Source, Advertiser Name, Brand Name, Line Item Name, Creative Name, Placement, Supply Source, Targeting Method and many more...

448

Metrics availables

94

Dimensions availables

Connect Amazon DSP to PostgreSQL in minutes

Move your data from Amazon DSP 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 Amazon DSP account

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

Client A · Connected sources
5 sources ready
Amazon DSP 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 Amazon DSP campaign delivery in SQL.

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

Amazon DSP.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.amazon_dsp_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.

Can Catchr send Amazon DSP records directly to PostgreSQL?

Add Amazon DSP in Sources and connect the existing PostgreSQL database in Storage. A datastream defines the route, while the job loads the chosen fields into "ad groups".

How much control do I have over Amazon DSP fields in PostgreSQL?

Select concrete Amazon DSP fields such as 3P Fees, 3P Pre Bid Fee, 3P Pre Bid Fee Double Verify, and Normalized Week of the year. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as accounts, advertisers, and campaigns.

How should I configure recurring Amazon DSP imports in PostgreSQL?

Define the first Amazon DSP fetch, run frequency, and lookback window in the "ad groups" job. Each scheduled run replaces data inside the configured period.

How do I prevent duplicate Amazon DSP rows in PostgreSQL?

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

How can a team use Amazon DSP data after it reaches PostgreSQL?

With Amazon DSP data, a PostgreSQL query can summarize spend, impressions, clicks, and click-through rate by campaign. Model 3P Fees and 3P Pre Bid Fee 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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