Supermetrics for Snowflake
Connect Facebook Ads to Snowflake — Elastic Ad Analytics with Zero Ops
Load your complete Facebook Ads history into Snowflake. Leverage time travel to audit changes, clone environments instantly for testing, share governed datasets with partners, and scale compute independently of storage — all while querying campaigns, creatives, and audiences with standard SQL and no ETL code.
Why Connect Facebook Ads to Snowflake?
Ads Manager gives you one view of your data with rigid date ranges. Warehouse your Facebook Ads data in Snowflake and unlock time travel, instant scaling, zero-copy cloning, and seamless data sharing — all with zero infrastructure management.
- Did your ROAS numbers change after Meta reprocessed attribution data? With Time Travel, you can run SELECT * FROM facebook_ads AT(TIMESTAMP => '2024-01-15 09:00:00'::TIMESTAMP) and compare the before and after snapshots side by side. This is invaluable for reconciling reported numbers with stakeholders who saw different values last week.
- Need to prototype a new dbt model that restructures your campaign hierarchy? Clone the production database with CREATE DATABASE staging CLONE production, run your experiments on the clone, and drop it when done. The clone shares the underlying micro-partitions with the original, so it costs nothing extra until you modify data.
- Your Facebook Ads data sits in cheap cloud storage regardless of compute activity. When your team needs to run heavy cross-channel attribution queries, spin up an XL warehouse for the job. When the dashboard is built, scale back to XS for routine refreshes. You only pay for compute seconds actually consumed.
- Agencies can share live campaign performance with clients by creating a Snowflake share that exposes specific views (e.g., campaign-level aggregates without creative-level detail). The consumer sees a live, always-current view without any ETL pipeline between the two accounts. Row-level security policies ensure each client sees only their own data.
- Some Facebook Ads fields — like targeting specs, action breakdowns, or creative thumbnails — are deeply nested JSON. Snowflake lets you store these as VARIANT columns and query them with dot notation (e.g., targeting:age_min::INT). This eliminates the need for complex pre-processing and preserves the full richness of the API response.
- As Supermetrics loads new Facebook Ads data daily, Snowflake's automatic clustering keeps the micro-partitions pruned and sorted by the columns you query most. For heavy workloads, you can define explicit clustering keys (e.g., date, campaign_name) to further accelerate range scans — but most teams never need to, because the defaults are already excellent.
How to Connect Facebook Ads to Snowflake
Three steps. Under two minutes. Zero code.
- 1
Create a data transfer
Log into Supermetrics, select your data source and Snowflake as your destination.
- 2
Authorize and configure
Connect your data source account, enter your Snowflake account identifier and warehouse details, choose your database and 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 Snowflake automatically.
Facebook Ads Data Schema in Snowflake
Supermetrics creates and maintains clean, typed tables automatically. Here's what your Facebook Ads data looks like in Snowflake.
Data Freshness & Scheduling
Facebook Ads data is typically available in Snowflake within 3-6 hours of the reporting period end. Schedule daily transfers to have yesterday's complete data ready each morning. Snowflake's automatic clustering keeps queries fast as your dataset grows. Historical backfill is available for up to 37 months.
What Facebook Ads Data Can You Pull into Snowflake?
Supermetrics gives Snowflake 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 Snowflake?
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 Snowflake — 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 the source and Snowflake as the destination. Authorize your Facebook Ads account, enter your Snowflake account identifier, warehouse, database, and schema details, select the fields you need, set a schedule, and start the transfer. No Snowpipe configuration or custom staging areas required — Supermetrics handles everything end to end. You can even spin up a dedicated Snowflake virtual warehouse for your marketing loads so they never compete with other workloads for compute.
- Supermetrics is SOC 2 Type II certified and fully GDPR compliant. All Facebook Ads credentials are encrypted at rest and in transit. Data flows directly from the Facebook Ads API into your Snowflake account — Supermetrics does not store your marketing data. Snowflake adds its own defense-in-depth: network policies restrict access by IP, role-based access control governs who can query which tables, and all data is AES-256 encrypted at rest with automatic key rotation. If something goes wrong, Snowflake Time Travel lets you restore tables to any point within your retention window.
- That is one of the most powerful reasons to use Snowflake. Once Facebook Ads data lands in your account, you can JOIN it with any other table — GA4 exports, CRM data, revenue tables — using standard SQL. Want to enrich your analysis further? Browse the Snowflake Marketplace for ready-to-query third-party datasets (demographics, weather, economic indicators) and combine them with your marketing data instantly — no ETL, no data movement. Supermetrics supports 170+ data sources that all land in the same Snowflake database, and Secure Data Sharing lets you publish governed datasets to partners or other business units without copying a single byte.
- All standard Facebook Ads reporting fields are available, including Impressions, Clicks, Spend, ROAS, CPA, CTR, and many more. You choose exactly which metrics and dimensions to transfer during setup, and you can modify the selection at any time without affecting historical data already loaded. Need to test a schema change? Use Snowflake's zero-copy cloning to create an instant clone of your marketing database, experiment freely, and drop the clone when you are done — no extra storage cost, no risk to production tables.
- Data freshness depends on your transfer schedule. Supermetrics supports hourly, daily, or weekly transfers into Snowflake. Most users run daily transfers so yesterday's complete data is ready each morning. Incremental loading ensures only new and updated records are transferred, keeping warehouse credits low and load times fast. Because Snowflake separates storage from compute, you can scale your virtual warehouse up during heavy load windows and back down afterward — paying only for the seconds of compute you actually use.
- Supermetrics maps Facebook Ads fields to Snowflake-native types. Dates become DATE, text fields like campaign_name are stored as VARCHAR, monetary metrics like spend use NUMBER(18,6) for sub-cent precision, and count metrics like impressions use NUMBER(38,0). The mapping is automatic — select your fields and Supermetrics creates the table with correct DDL.
- Yes. By default, Snowflake retains 1 day of Time Travel data (up to 90 days on Enterprise edition). You can query your Facebook Ads table as it existed at any past timestamp using AT or BEFORE clauses. This is especially useful for auditing when Meta reprocesses attribution data and your numbers shift retroactively.
- When you run CREATE TABLE facebook_ads_staging CLONE facebook_ads, Snowflake creates a metadata-only copy that shares the underlying micro-partitions with the original. The clone is instant, costs no additional storage, and is fully independent — writes to the clone do not affect the original. This is ideal for testing dbt models, new attribution logic, or BI prototyping.
- Absolutely. Create a Snowflake share with a secure view that filters by client or account ID, then grant access to the client's Snowflake account. They see live, always-current data without any file transfers or scheduled exports. You control exactly which rows and columns are visible using Snowflake's column-level and row-level security policies.
- Snowflake charges separately for storage and compute. Storage costs roughly $23-$40 per TB per month depending on cloud and region — and most Facebook Ads datasets are well under 10 GB. Compute is billed per-second when your virtual warehouse is active. A typical daily transfer on an XS warehouse uses a few cents worth of credits. The total monthly cost for most teams is under $10.
- Yes. The Facebook Ads API covers all Meta ad placements including Instagram Feed, Stories, Reels, and Explore. Data lands in the same Snowflake table with a placement column. Filter with WHERE placement ILIKE '%instagram%' for Instagram-only analysis, or query without filters for a combined Meta Ads view.
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