Connect Facebook Ads to Azure SQL Database — Enterprise Ad Data in Azure

Log into the Supermetrics Hub, create a new data transfer, select Facebook Ads as the source and Azure SQL Database as the destination. Authorize your Facebook Ads account, provide your Azure SQL connection string, choose the fields you want, set a schedule, and start the transfer. Supermetrics writes data using optimized T-SQL bulk operations, so no custom ETL code, stored procedures, or Azure Data Factory pipelines are required — tables are created and managed automatically with full SQL Server compatibility.

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 to your own Azure SQL Database — Supermetrics does not store your marketing data on its servers. Azure SQL Database provides multiple security layers: Transparent Data Encryption (TDE) encrypts data at rest automatically, Azure AD authentication replaces passwords with enterprise identity, row-level security restricts which teams see which data, and Advanced Threat Protection monitors for anomalous access patterns. Your marketing data gets the same enterprise security as any mission-critical Azure workload.

That is one of the biggest advantages of storing marketing data in Azure SQL Database. Once Facebook Ads lands in your database, you can JOIN it with any other table — CRM records, ERP data, product catalogs, other ad platforms — using familiar T-SQL, the same query language your team already knows from SQL Server. Because Azure SQL Database is fully compatible with the SQL Server ecosystem, you can connect Power BI, SSRS, Excel, or any ODBC/JDBC tool directly. Supermetrics supports 170+ data sources that can all land in the same database for unified analysis.

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. Azure SQL Database supports columnstore indexes for analytics workloads — if your Facebook Ads tables grow large, adding a clustered columnstore index can speed up aggregation queries by 10x or more, bringing warehouse-class performance to a managed relational database.

Data freshness depends on your transfer schedule. You can run transfers hourly, daily, or weekly. Most users schedule daily transfers so yesterday's complete data is ready each morning. Supermetrics uses incremental loading — only new and updated records are transferred — so even large accounts refresh quickly. Azure SQL Database scales compute independently of storage, so you can temporarily bump to a higher service tier during peak load windows and scale back down when transfers finish, keeping costs predictable.

Supermetrics creates clean, properly typed tables in your Azure SQL Database. Dates are stored as DATE, text fields like campaign_name as NVARCHAR, and numeric metrics like impressions and spend as FLOAT or INT. You choose which fields to include during setup, and each transfer creates or updates tables in your chosen database and schema.

Supermetrics supports backfilling up to 37 months of historical data from the Facebook Ads API, which is the maximum retention window Meta provides. The historical data uses the same table schema as ongoing transfers, so all your T-SQL queries work across the full date range.

Supermetrics uses incremental loading by default. Each scheduled transfer fetches only new and updated records since the last run, then inserts or updates them in your Azure SQL tables. This keeps transfer times short and database load low. You can also trigger a full refresh for a specific date range when needed.

Most Facebook Ads datasets are small enough for the Basic or Standard tier — even large accounts with years of history rarely exceed a few GB. The Standard tier (S0 or S1) is sufficient for most marketing analytics workloads. You can always scale up to a higher tier if you add more data sources or heavier query workloads.

Yes, and this is one of the main reasons organizations choose Azure SQL for marketing data. Use UTM parameters to join Facebook Ads clicks with CRM leads, then extend the chain to revenue tables using deal IDs or customer emails. A typical T-SQL JOIN matches campaign names to CRM lead sources to calculate true cost-per-acquisition through to closed revenue.

Yes. The Facebook Ads API covers all Meta ad placements including Instagram Feed, Stories, Reels, and Explore. You can filter by placement in your T-SQL queries to isolate Instagram-specific performance, or aggregate across all placements for a unified Meta Ads view.