PostgreSQL Connector

Use Postgres data for AI pipelines with automatic synchronization.

Setup Instructions

1. Navigate to Data Integrations

Go to the Data Integrations tab in your flow.

2. Select PostgreSQL Integration

Click Select an Integration, type PostgreSQL in the search, and click Connect.

3. Configure Connection Settings

Fill in the following database connection details:

• Connector Name: Give your connector a descriptive name
• Host: The hostname or IP address of your PostgreSQL server
  • For local setup: localhost or 127.0.0.1
  • For remote databases: The full hostname (e.g., db.example.com or your-instance.region.rds.amazonaws.com)
• Port: The PostgreSQL port (default is 5432)
• Database Name: The name of the database you want to connect to
• Username: Your PostgreSQL username
• Password: Your PostgreSQL password
• Folder (Optional): Select a destination folder in the file manager
  • If not specified, data will be stored in the root directory

4. Configure SSL Settings

Important Security Note:

• SSL Enabled: For production and internet-facing databases, always enable SSL to ensure secure data transmission
• SSL Disabled: Only disable SSL for local development environments where security is not a concern

For production databases:

1. Enable the Use SSL checkbox
2. Ensure your PostgreSQL server is configured to accept SSL connections
3. This guarantees encrypted data transmission and protects sensitive information

For local development:

• You may disable SSL for convenience when connecting to localhost

5. Create the Connection

After filling in all connection details, click Create Connection.

The system will:

• Test the database connection
• Verify credentials and permissions
• Begin the initial data synchronization

6. Monitor Sync Status

1. Navigate to Data Synchronization to see the import progress
2. The connector will download all tables from your PostgreSQL database
3. Each table will be imported as a separate file

7. Access Your Data

1. Once the sync is complete, go to File Manager
2. Navigate to the folder you specified (or root directory)
3. You'll see all tables from your database as individual files
4. Click on any file to preview the table data
5. The data is now ready to use in your AI pipelines and flows

What Gets Imported:

• All tables in the specified database
• Complete table data with all rows and columns
• Table structure is preserved in a standardized format

Best Practices:

• Always use SSL for production databases to ensure data security
• Use read-only database users when possible to prevent accidental modifications
• For large databases, consider creating a dedicated read replica to avoid impacting production performance
• Regularly monitor sync jobs to ensure data stays up-to-date