SQL Server Connector
Use SQL Server, Azure SQL Database, or Microsoft Fabric Warehouse as a source or destination for replication and activation workflows.
Evaluating against Fivetran? See how Supaflow handles SQL Server pricing, connector quality, and Snowflake deployment side-by-side.
Supaflow vs FivetranLoad SQL Server into Snowflake
Dedicated pages for destination-specific setup, buyer questions, and Snowflake sync behavior.
Why Supaflow
All connectors included
Every connector is available on every plan. Pricing does not increase with connector count.
Pay for compute, not rows
Credit-based pricing. Usage scales with your pipelines, not with row counts.
One platform
Ingestion, dbt Core transformation, reverse ETL, and orchestration in a single workspace.
Capabilities
Sources, Destinations, and Activation
Read accessible tables for ingestion or activation pipelines, or load supported source data into schemas and tables managed by the connector.
SQL Password or Microsoft Entra Authentication
Use SQL password credentials for SQL Server, or a Microsoft Entra service principal for Azure SQL Database and Fabric Warehouse. Encrypted connections are enabled by default.
Standard and Change Tracking Reads
Use a reliable cursor column for incremental reads, or enable SQL Server Change Tracking to capture inserts, updates, and deletes. Fabric Warehouse uses Standard mode only.
Resumable Large-Table Loads
Large tables load in bounded, resumable batches, so an interrupted initial sync picks up where it left off instead of restarting. Batch size is tunable, with an optional memory-aware mode for very wide rows.
Microsoft Fabric Warehouse Support
Use the same SQL Server connector for Fabric Warehouse, with automatic endpoint detection, Fabric-compatible SQL behavior, and service-principal initialization.
Supported Objects
Source Objects
Tables
Accessible SQL Server, Azure SQL, and Fabric Warehouse tables.
Schemas
Schemas visible to the configured database identity.
Destination Objects
Destination tables
Pipeline output loaded into connector-managed schemas and tables.
Change Tracking (when enabled)
Tracked tables
Tables with SQL Server Change Tracking enabled and a primary key.
Delete markers
Deleted rows can be marked in the destination for downstream handling.
How It Works
Prepare database access
Create a dedicated read identity for a source or grant schema and table write access for a destination. Configure the SQL Server or Azure SQL firewall when inbound access is restricted.
Enable Change Tracking (optional)
For SQL Server or Azure SQL Change Tracking mode, enable it on the database and each selected table. Every tracked table needs a primary key and the connector identity needs permission to view changes.
Choose authentication
Use SQL Password where appropriate, or create a Microsoft Entra service principal for Azure SQL Database or Fabric Warehouse. Fabric also requires its workspace ID and workspace access.
Test and save
Enter the host, port, database, authentication, query mode, and encryption settings, then click Test & Save. Fabric endpoints are detected automatically from their standard hostname.
Use Cases
SQL Server to Snowflake replication
Replicate SQL Server tables into Snowflake with cursor-based or Change Tracking incremental sync for near-real-time analytics.
Azure SQL Database offloading
Move reporting workloads off Azure SQL by syncing data into a warehouse, reducing DTU consumption on your production database.
Delete detection with Change Tracking
Use Change Tracking mode to capture hard deletes in SQL Server. Deleted rows are marked in the destination, enabling soft-delete patterns in your warehouse.
Reverse ETL back to SQL Server
Write enriched or aggregated data into SQL Server, Azure SQL Database, or Fabric Warehouse for operational and reporting workflows.
Activate warehouse data
Use curated SQL Server, Azure SQL, or Fabric Warehouse tables as the source for activation pipelines that update supported business applications.
Frequently Asked Questions
How do I connect Supaflow to an on-premises SQL Server?
For production, deploy a self-hosted Docker Agent on a stable host inside the same private network as SQL Server. The agent connects to SQL Server over the private network and polls Supaflow over outbound HTTPS, so the database port stays private. For a quick proof-of-concept connectivity test, you can use a temporary ngrok or bore TCP tunnel; do not use a temporary public tunnel for production or sensitive data.
Which SQL Server versions are supported?
SQL Server 2016 or higher, Azure SQL Database, and Microsoft Fabric Warehouse are supported. SQL Server Change Tracking applies to SQL Server and Azure SQL Database, not Fabric Warehouse.
Can I use SQL Server as a destination?
Yes. Supaflow can load data from supported sources into SQL Server, Azure SQL Database, or Fabric Warehouse. The destination identity needs permission to create and update its target schemas and tables.
What is the difference between Standard and Change Tracking modes?
Standard mode uses a cursor column (timestamp) to detect inserts and updates but cannot detect deletes. Change Tracking mode uses SQL Server built-in change tracking to capture all changes including deletes.
Do I need to whitelist an IP address?
If SQL Server or Azure SQL Database restricts inbound connections, allow the hosted Supaflow agent address documented in the setup guide. Private agents need network access from their own environment. Fabric Warehouse follows your Fabric tenant network policy and uses TCP port 1433.
What happens to tables without Change Tracking enabled?
Tables without Change Tracking enabled are automatically skipped during schema discovery in Change Tracking mode. Enable Change Tracking on each table you want to sync.
Where is the Microsoft Fabric setup guide?
Microsoft Fabric Warehouse uses this SQL Server connector with Microsoft Entra service-principal authentication. The Fabric guide covers tenant settings, workspace roles, the Warehouse SQL endpoint, and the workspace ID.
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