Connect Facebook Ads to Amazon Redshift — Full-Funnel Ad Intelligence on AWS

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.