Connecting a PostgreSQL database to your project is a key step in leveraging the powerful capabilities of Streamline. This guide walks you through the process of integrating a PostgreSQL data source and creating datasets for use in your workflows.
Note: This article is specific to PostgreSQL. If you're connecting a different data source, check our Data Source Library for platform-specific instructions.
Part 1: Connect to a PostgreSQL Data Source
Step 1: Go to the Integration Page
From your dashboard, navigate to the Integrations tab.
Click + Add New connection on the right side of the page.
Step 2: Select PostgreSQL as Your Data Source Type
In the pop-up window, choose PostgreSQL from the list of supported databases.
Give your connection a recognizable name & description (e.g., Production PostgreSQL, Reporting DB).
Tip: Pick a name that helps team members quickly identify the database’s purpose or environment.
Step 3: Enter PostgreSQL Connection Details
Input the following credentials for your PostgreSQL instance:
-
Host (e.g.,
db.example.com) - Port
- Username and Password
Once you've entered the details, click Next to test the connection.
Step 4: Choose Your Database and Schema
Once authenticated, the platform will ask you to specify which database and schema within that database you would like to connect to.
Step 5: Finalize the Connection
Click Connect to complete the integration. Your PostgreSQL connection will now appear in the Integration list.
Step 6: Explore Your PostgreSQL Data
Once connected:
- Visit the Data Catalog to explore entities (tables) and fields available in your PostgreSQL schema. The Data Catalog tab can be found on the left-hand panel under the Data section.
- Use filters or the search box to locate specific data elements.
The Entity View displays tables, while the Data Field View lists individual columns with metadata like type and source.
Example of Data Fields View
Part 2: Create and Manage a Dataset from PostgreSQL
Once your PostgreSQL connection is active, you can start organizing your data into reusable datasets for your projects and workflows.
Step 1: Access the Datasets Section
Navigate to Datasets from the left-hand panel. Click + Create New Dataset.
Step 2: Define Dataset Basics
Name your dataset clearly.
Select your PostgreSQL data source. Choose a Primary Entity (table) from your PostgreSQL schema. Assign a label to translate internal database terms into more user-friendly language. Example: Use "Customer Info" instead of tbl_customer_data.
Step 3: Configure Field Access
On the next screen, review each field (column) and configure write access if needed.
Once ready, click Create to save the dataset.
Optional: Create a Dataset Directly from the Data Catalog
You can also build a dataset directly from the PostgreSQL schema view:
In the Data Catalog, select an entity (table) & click New Dataset from Entity.
Customize the dataset by selecting fields or updating their classifications.
Optional: Add Related Entities
Want to enrich your dataset?
While creating a dataset, click Add Related Entity to include related tables (e.g., orders linked to customers).
The platform uses foreign key relationships to map them automatically.
You can add as many related entities as needed before finalizing the dataset.
Optional: Edit an Existing Dataset
To update a dataset:
Go to Datasets, locate the dataset, and click Edit.
You can:
- Add/remove related entities
- Change labels or field classifications
- Update data access settings
Click Next & Update to save changes.
Summary
By connecting your PostgreSQL database and building tailored datasets, you ensure that your data is clean, accessible, and structured for workflows.
Need help? Check out our help centre for more article or reach out to our Support team.
Comments
0 comments
Article is closed for comments.