Meta Ads (Facebook Ads)Redshift

Meta Ads (Facebook Ads) + Redshift

Facebook Ads is an online advertising platform developed by Facebook that lets businesses and advertisers create ad campaigns for delivery across multiple placements like News Feed, Stories, video, and mobile apps. Amazon Redshift, on the other hand, is a cloud data warehouse designed for fast, efficient analysis of large data volumes

With Erathos, you can integrate Facebook Ads data into Redshift in just a few minutes. Our platform handles the entire data movement process into your analytics environment and lets you blend that data with other sources in your data warehouse. That way, your time is focused on what actually drives 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.

What Facebook Ads data does Erathos sync with Redshift?

The integration automatically syncs the main Facebook Ads objects:

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

Why sync Facebook Ads with Redshift?

Ad platforms like Facebook Ads surface channel metrics, but not the real business impact. Centralizing the data in Redshift lets you calculate true ROAS (based on revenue, not platform conversions), compare performance across channels using the same methodology, and tie media spend to the customer lifecycle end to end.

How it works

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

Why companies move data from Facebook Ads to Redshift with Erathos

Centralizing Facebook Ads data in Redshift has never been easier

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

Why do data teams choose Erathos for Facebook 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 Facebook 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 Sets, Creatives, Impressions, Clicks, Conversions, and Spend from Facebook Ads to Redshift. 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 sync—only new or updated records are processed in each run, keeping the Facebook Ads pipeline efficient and Redshift 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 Facebook Ads to Redshift and start syncing immediately—no credit card required.

Data ingestion with control, observability and scale