Supermetrics for Amazon Redshift
Connect Facebook Ads to Amazon Redshift — Full-Funnel Ad Intelligence on AWS
Load your complete Facebook Ads history into Amazon Redshift. Query campaigns, audiences, and creatives with familiar SQL, join with Spectrum external tables for cross-source attribution, and feed results directly into QuickSight, Tableau, or any JDBC-compatible tool — all without writing a single line of ETL code.
Why Connect Facebook Ads to Amazon Redshift?
Ads Manager caps your analysis at 37 months and 250 columns. Move your Facebook Ads data into Amazon Redshift and unlock unlimited SQL-powered analytics inside the AWS ecosystem you already rely on.
- Because Redshift shares IAM roles, VPC networking, and S3 access with the rest of your AWS infrastructure, there are no cross-cloud data egress fees and no credential sprawl. Load Facebook Ads data once, and every AWS service can consume it through standard JDBC/ODBC connections or Redshift Data API calls.
- Redshift Spectrum lets you run JOIN queries across your loaded Facebook Ads tables and external S3 data using the same SQL endpoint. Compare ad spend to S3-hosted web analytics logs, product catalog feeds, or data lake exports from other tools without any ETL pipeline in between.
- Monday-morning dashboard rushes, end-of-quarter reporting sprints, and ad-hoc executive deep dives all hit the cluster simultaneously. Concurrency Scaling spins up additional compute in seconds and routes overflow queries there — your SLA stays consistent, and you only pay for the burst capacity you actually use.
- A typical Facebook Ads table might have 30+ columns, but most dashboard queries touch only 4-5 of them. Redshift columnar storage and zone maps mean the engine reads just the blocks it needs, compressing I/O by 10-100x compared to row-oriented databases. Add SORTKEY on date and DISTKEY on campaign_name to make your most common queries even faster.
- Instead of re-running heavy GROUP BY queries every time a dashboard loads, create a materialized view once. Redshift incrementally maintains it as new Facebook Ads rows land, so your BI tool reads pre-computed results in milliseconds. This is especially valuable for cross-source attribution views that join Facebook Ads with other large tables.
- Every transfer creates Redshift tables with properly typed columns — DATE for dates, VARCHAR for text fields, DECIMAL for monetary values, BIGINT for count metrics. Schema changes from the Facebook Ads API are detected and applied automatically. You focus on querying; Supermetrics handles the plumbing.
How to Connect Facebook Ads to Amazon Redshift
Three steps. Under two minutes. Zero code.
- 1
Create a data transfer
Log into Supermetrics, select your data source and Amazon Redshift as your destination.
- 2
Authorize and configure
Connect your data source account, provide your Redshift cluster endpoint and credentials, choose your schema, and select the data you want to transfer.
- 3
Set schedule and start transfer
Choose your refresh frequency (hourly, daily, or weekly) and click Start. Your data begins flowing into Redshift via S3 COPY automatically.
Facebook Ads Data Schema in Amazon Redshift
Supermetrics creates and maintains clean, typed tables automatically. Here's what your Facebook Ads data looks like in Amazon Redshift.
Data Freshness & Scheduling
Facebook Ads data is typically available in Redshift within 3-6 hours of the reporting period end. Schedule daily transfers to have yesterday's complete data ready each morning. Supermetrics stages data via S3 COPY for maximum throughput. Historical backfill is available for up to 37 months.
What Facebook Ads Data Can You Pull into Amazon Redshift?
Supermetrics gives Amazon Redshift access to your full Facebook Ads reporting data — metrics and dimensions you already know from the Facebook Ads interface.
Key Metrics
- Impressions
- Clicks
- Spend
- ROAS
- CPA
- CTR
- CPM
- Conversions
- Reach
- Frequency
- Video views
- Link clicks
- Cost per result
- Purchase value
- Add to cart
Key Dimensions
- Campaign name
- Ad set name
- Ad name
- Age
- Gender
- Placement
- Device
- Country
- Region
- Platform
- Objective
- Delivery status
- Creative ID
Resources & Guides
Marketing data warehousing 101
Build vs. buy: data pipeline decisions
The marketing analytics roadmap
How to optimize your Facebook ad campaigns
Facebook Ads report templates
PPC reporting: extract insights from paid campaigns
Why Supermetrics for Amazon Redshift?
Purpose-built for marketing data since 2009. 200,000+ companies trust Supermetrics to move 15% of global ad spend into reporting and analytics destinations.
No Vendor Lock-In
Your data lands in Amazon Redshift — infrastructure you own and control. Use any BI tool, any transformation layer, any ML platform. If you ever switch providers, your data and dashboards stay with you.
170+ Marketing Data Sources
Purpose-built for marketing data — not a generic ETL tool. Supermetrics covers 99% of metrics and dimensions from each source, with pre-structured tables ready for analysis. No transformation layer required.
Managed Schema
Supermetrics creates and maintains your Facebook Ads tables automatically. Schema changes from the source API are handled for you — no broken pipelines, no manual migrations.
Your Data, Your Infrastructure
Supermetrics moves data directly to your destination — nothing is stored on our servers. SOC 2 Type II certified, GDPR and CCPA compliant. Your data stays in infrastructure you control, simplifying privacy and compliance reviews.
Flat-Rate, Predictable Pricing
Fixed annual pricing regardless of data volume — no per-row charges, no surprise bills during peak campaign seasons. Transfer as much Facebook Ads data as you need without worrying about cost spikes.
No Data Limits
Query any date range, any number of campaigns, any level of granularity. No row limits, no sampling, no restrictions on the data you can pull.
Frequently Asked Questions
- Log into the Supermetrics Hub, create a new data transfer, select Facebook Ads as your source and Amazon Redshift as the destination. Authorize your Facebook Ads account, provide your Redshift cluster endpoint and credentials, choose your target schema and table naming conventions, select the fields you need, set a schedule, and start the transfer. Supermetrics loads data using optimized S3 COPY commands — the same high-throughput path AWS recommends for bulk ingestion — so no custom ETL pipelines, AWS Glue jobs, or staging buckets are required.
- Supermetrics is SOC 2 Type II certified and GDPR compliant. All Facebook Ads credentials are encrypted at rest and in transit using TLS 1.2+. Data flows directly from the Facebook Ads API to your Redshift cluster — Supermetrics never stores your marketing data on its own servers. On the AWS side, your VPC isolation keeps the cluster off the public internet, IAM policies restrict which roles can access the data, and S3 server-side encryption protects any intermediate staging objects. You retain full control of your security perimeter.
- Absolutely — cross-source analysis is where Redshift shines in the AWS ecosystem. Once Facebook Ads data lands in your cluster, you can JOIN it with any other table in the same schema. Need to enrich it with raw event logs or clickstream data sitting in S3? Redshift Spectrum lets you query those external files directly without loading them, so your cluster stays lean while your analysis spans petabytes. Supermetrics supports 170+ data sources that all land in the same Redshift schema, and you can optimize JOIN performance further with DISTKEY and SORTKEY settings on frequently queried columns.
- All standard Facebook Ads reporting fields are available, including Impressions, Clicks, Spend, ROAS, CPA, CTR, and many more. You select exactly which metrics and dimensions to transfer during setup, and you can add or remove fields at any time without losing historical data already loaded into Redshift. Because Redshift uses columnar storage, queries that scan only a few selected metrics out of a wide table are extremely fast — the engine skips unneeded columns at the disk level, reducing I/O and keeping your analytics snappy.
- Data freshness depends on your transfer schedule. Supermetrics supports hourly, daily, or weekly transfers into Redshift. Most teams schedule daily transfers so yesterday's final numbers are ready each morning. Incremental loading means only new and changed records are written via optimized S3 COPY commands, keeping cluster load minimal. If you define a SORTKEY on your date column, Redshift can skip entire disk blocks during time-range queries, making your morning dashboards in QuickSight or Tableau load in seconds.
- Supermetrics maps Facebook Ads fields to Redshift-native types. Dates become DATE, text fields like campaign_name are stored as VARCHAR(512), monetary metrics like spend use DECIMAL(18,6) for cent-level precision, and count metrics like impressions use BIGINT. The mapping is automatic — you choose the fields, and Supermetrics creates or alters the table with the correct DDL.
- Yes. Your Facebook Ads data lives in standard Redshift tables, and Redshift Spectrum lets you query external tables backed by S3 in the same SQL statement. A single query can JOIN your facebook_ads table with a Parquet-based GA4 export in S3, giving you cross-source attribution without loading everything into the cluster.
- For most Facebook Ads workloads, set date as the SORTKEY and campaign_name (or campaign_id) as the DISTKEY. This layout accelerates the two most common query patterns: filtering by date range and grouping by campaign. If your queries frequently filter by ad_set_name or placement instead, adjust the DISTKEY accordingly. Supermetrics creates sensible defaults, and you can ALTER the keys later without re-loading data.
- Supermetrics stages data in S3 and uses the Redshift COPY command for maximum throughput. COPY is significantly faster than row-by-row INSERT because it parallelizes the load across all cluster slices. The staged S3 files are temporary and automatically cleaned up after a successful load.
- Redshift pricing depends on your cluster type and size. On RA3 nodes with managed storage, you pay roughly $0.024 per GB-month for data stored — comparable to S3. Facebook Ads datasets are typically small (a few GB even for large accounts with years of history), so the incremental storage cost is minimal. The bigger factor is compute — right-size your cluster to your query workload, not your data volume.
- Yes. The Facebook Ads API covers all Meta ad placements including Instagram Feed, Stories, Reels, and Explore. The data lands in the same Redshift table with a placement column you can filter on. Use WHERE placement LIKE '%instagram%' to isolate Instagram-specific performance, or leave it unfiltered for a unified Meta Ads view.
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