Destinations
Connect to data warehouses, data lakes, and databases where your synced data will be loaded.
What are Destinations?
Destinations are target systems where Supaflow loads your ingested data. Once connected, you can create pipelines that sync data from sources into these destinations.
To add a destination:
- Navigate to Destinations in the sidebar
- Click + New Destination
- Select your connector type
- Follow the connector-specific setup guide below
- Click Test & Save
Available Destination Connectors
Cloud Data Warehouses
Snowflake Cloud data warehouse with native integration. Supports key-pair authentication and automatic schema creation.
Amazon Redshift Cloud data warehouse from AWS. Supaflow loads pipeline data into Redshift for analytics and downstream workflows.
Google BigQuery Cloud data warehouse from Google Cloud. Supaflow loads pipeline data into BigQuery through a customer-owned Cloud Storage staging bucket.
Databricks Lakehouse destination for loading pipeline data into Unity Catalog tables through a Databricks SQL warehouse and existing volume.
Cloud Storage & Data Lakes
Google Drive Write pipeline output as CSV files, native Google Sheets, or Excel workbooks in Google Drive. Also available as a source.
SharePoint Write pipeline output as CSV files or Excel workbooks in SharePoint Online or OneDrive for Business. Also available as a source.
Amazon S3 Data Lake Load data as Parquet files or Apache Iceberg tables to Amazon S3. Supports AWS Glue and Snowflake Open Catalog for querying with Athena, Spark, Snowflake, and other analytics engines.
Amazon S3 (Legacy) Load data as Parquet files to Amazon S3 with optional AWS Glue Data Catalog integration for querying with Athena.
Databases
PostgreSQL Open-source relational database. Supaflow creates and manages its own schema and tables in your database. Also available as a source.
SQL Server Microsoft SQL Server and Azure SQL Database. Supaflow creates and manages its own schemas and tables in your database. Also available as a source.
Schema Management
Each pipeline gets a unique schema prefix (e.g., salesforce, hubspot_2) that determines where data is loaded:
- Sources without schemas (Salesforce, HubSpot): Prefix becomes the schema name
- Sources with schemas (PostgreSQL): Prefix is prepended to source schema names
Supaflow automatically creates target schemas in your destination warehouse.
Next Steps
After connecting a destination:
- Add a Source - Choose where to pull data from
- Create a Pipeline - Configure what data to sync
- Monitor Activities - Track pipeline execution
Support
Need help? Contact us at support@supa-flow.io
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