Google AdsPostgreSQL

Google Ads + PostgreSQL

Google Ads is Google's online advertising platform, allowing businesses and advertisers to build ad campaigns across formats such as Search, Display, Video, and mobile apps. PostgreSQL, in turn, is a highly robust, scalable open-source relational database management system. It supports a broad range of data types and advanced features.

With Erathos, you can load Google Ads data into PostgreSQL in minutes. Our platform handles the entire movement of data into your analytics environment and lets you combine it with other sources in your Data Warehouse. That way, your time goes toward what actually creates value — uncovering actionable insights and making more data-driven decisions.

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Simplified extraction and ingestion

Move data in a few clicks

1

Connect your source

Authenticate your account and you're done. 100+ ready-made connectors, no code required.

2

Configure the sync

Pick the tables, the schedule and the update type: batch, cursor-based incremental or CDC.

3

Choose your destination

Load into BigQuery, Redshift, Databricks, PostgreSQL, ClickHouse, Amazon S3 and more.

Which Google Ads data does Erathos sync to PostgreSQL?

The integration automatically syncs the main Google Ads objects:

  • Campaigns — status, budget, date range, and settings
  • Ad groups — targeting, bids, and performance
  • Creatives — ad copy, images, and creative-level metrics
  • Impressions and clicks — daily reach and engagement data
  • Conversions — conversion events and value per action
  • Spend — spend by campaign, ad group, and time period

Why sync Google Ads with PostgreSQL?

Ad platforms like Google Ads show channel metrics, but not the real business impact. Centralizing the data in PostgreSQL lets you calculate true ROAS (based on revenue, not the platform's conversions), compare performance across channels with the same methodology, and tie media spend to the full customer lifecycle.

How it works

Erathos connects to Google Ads through the official API and syncs your data incrementally — only new or updated records are processed on each run, keeping pipelines fast and PostgreSQL costs predictable. You choose the sync frequency (from every 5 minutes to daily), which objects to sync, and the destination dataset. Each run is logged with full observability: execution time, rows processed, errors with context, and instant alerts via Slack or email if anything goes wrong.

Why companies are moving Google Ads data into PostgreSQL with Erathos

Centralizing Google Ads data in PostgreSQL has never been easier.

Erathos is a data ingestion platform for data-driven marketing teams. With the Google Ads connector, you can automatically centralize impressions, clicks, conversions, and campaign spend in PostgreSQL—with full observability for every run and real-time alerts.

Why do data teams choose Erathos for Google Ads?

Data in your data warehouse in minutes

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Building data-driven stories

Every new source implementation, if I had to do it myself, would take about two or three months. With Erathos, it's done in a few hours. I don't need the skills of a data engineer to generate real value from the company's data.

Bruno Rosso
Bruno RossoData Analyst, Brick Software

Erathos revolutionized data management at WE. By integrating multiple SaaS tools into a single DW, our technical team now focuses on the core business. We implemented dashboards with insights across every area, enriching our organizational culture and improving our decision-making.

Matheus Nunes
Matheus NunesCTO & co-founder, WePayments

We used to have a lot of rework, and now we don't. It's more efficient to work this way. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.

Carlos Schwabe
Carlos SchwabeCo-Founder & CDO, Brick

If I didn't have this infrastructure, I'd need three or four people to do what Erathos does today. I was able to generate real value from my data with a much leaner setup than I thought I'd need. That's the core of building a data-driven culture: the team only uses data when they can trust it.

Thiago Paz
Thiago PazCFO, Brick

Erathos brought a practical turnaround at CCM. We were able to integrate financial systems, CRM, and processes with BigQuery in just a few clicks, with no technical team required. That gave us a reliable data warehouse that powers automations, dashboards, and even our customer service bots.

Gustavo Loforte
Gustavo LoforteTechnology Manager, CCM Group

The robustness and efficiency of Erathos's connectors — whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul — make the whole process much faster and more reliable. The technical documentation is extremely well put together and intuitive, which makes implementation much easier.

Sayuri Valente
Sayuri ValenteProject Manager, Xperiun
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FAQ

Frequently Asked Questions

Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like Google Ads to their data warehouse—with full observability into every run, zero maintenance, and none of the opacity of traditional market tools.

Erathos syncs Campaigns, Ad Groups, Creatives, Impressions, Clicks, Conversions, and Spend from Google Ads to PostgreSQL. Audience, targeting, and creative-level performance data are also available.

You can configure synchronization frequency from every 5 minutes up to daily, at the table level. Erathos uses incremental synchronization—only new or updated records are processed in each run, keeping your Google Ads pipeline efficient and your PostgreSQL costs predictable.

Erathos automatically detects failures and sends alerts to your email, Slack, or Discord with full context—not just "job failed." Smart retries handle transient errors, and every execution is logged with run time, processed rows, and error context so your team can debug in minutes, not hours.

Yes. Every Erathos connector includes a 14-day free trial. Connect Google Ads to PostgreSQL and start syncing immediately—no credit card required.

Data ingestion with control, observability and scale