Add Source Datastore
This guide walks you through creating a new source datastore on the Add Datastore page by setting up a new connection from scratch with your own credentials. To reuse a connection you already saved, see Adding a New Datastore Using an Existing Connection.
Connector-Specific Fields
The connection fields vary depending on the connector you select. This page covers the general flow for each connector family. For connector-specific field details, refer to the individual connector page (e.g., PostgreSQL, Snowflake, Amazon S3). The same content is also available while you work: the User Guide panel on the right side of the page shows the setup guide for whichever connector you select, and you can collapse it with the arrow button on its edge or open the page in a new tab.
Field reference
Besides the connection fields, which belong to the connector you select, every source datastore shares the fields below. Pick the tab that matches your connector family.
For relational databases and warehouses, the Datastores Extraction group asks for the Database and the Schema the datastore covers, followed by the Datastore Properties:
| REF. | REQUIRED | DESCRIPTION |
|---|---|---|
| 1 | Name Template: defines the naming pattern for each source datastore being created, combining the template with the schema name (e.g., dev_{{schema}}_sales). Left empty, the datastore is named from the connection name and the schema. |
|
| 2 | Group: organizes your datastores under a shared group in the navigation tree. Turn on Add New Group to create a new group instead of selecting an existing one. | |
| 3 | Teams: one or more teams to associate with this source datastore. | |
| 4 | Initiate Sync: automatically sync the datastore to detect containers and fields right after creation. |
Multiple schemas
On connectors that support it, selecting more than one schema creates one source datastore per schema, named from the Name Template. See Multi-Schema Source Datastore Creation for details.
For cloud object storage, the Datastores Extraction group asks for the path the datastore reads from, followed by the same Datastore Properties:
| REF. | REQUIRED | DESCRIPTION |
|---|---|---|
| 1 | Root Path: the folder inside the storage location that the datastore reads from. Use / to read from the root. |
|
| 2 | Name Template: defines the naming pattern for each source datastore being created, combining the template with the folder name (e.g., rides_{{path}}). Left empty, the datastore is named from the connection name and the path. |
|
| 3 | Group: organizes your datastores under a shared group in the navigation tree. Turn on Add New Group to create a new group instead of selecting an existing one. | |
| 4 | Teams: one or more teams to associate with this source datastore. | |
| 5 | Initiate Sync: automatically sync the datastore to detect containers and fields right after creation. |
Multiple folders
Selecting more than one folder creates one source datastore per folder, named from the Name Template.
Steps
Use this flow for relational databases and warehouses, such as PostgreSQL, Snowflake, or SQL Server.
Step 1: Click Add Source Datastore at the top-right of the Source Datastores page.
First datastore
On a deployment with no source datastores yet, Qualytics shows a welcome page instead of the datastore list. Its Connect your data button opens the same Add Datastore page.
Step 2: Select New Connection next to the search field, then select your JDBC connector from the grid. Use the search field to filter by name.
Step 3: Fill in the Connection Properties (a Connection Name that other datastores can reuse later, the connector's connection fields, and optionally Secrets Management to retrieve credentials from a secrets manager), the Datastores Extraction fields, and the Datastore Properties described in the Field reference. Then click Test connection.
Step 4: A success message confirms that the connection has been verified. Click Finish to create the datastore.
Info
The Finish and Next buttons stay disabled until the connection test passes on the current values. If you change a connection field after a successful test, test again. If the test fails, check the connector's troubleshooting page.
Tip
To link an enrichment datastore so Qualytics can store anomalies and metadata from the first operation, click Next instead of Finish. See Link Enrichment on Datastore Creation.
Step 5: A success dialog confirms that your datastore has been added. Click Go to your datastore to open its page.
Use this flow for cloud object storage, such as Amazon S3, Azure Data Lake Storage, or Google Cloud Storage.
Step 1: Click Add Source Datastore at the top-right of the Source Datastores page.
First datastore
On a deployment with no source datastores yet, Qualytics shows a welcome page instead of the datastore list. Its Connect your data button opens the same Add Datastore page.
Step 2: Select New Connection next to the search field, then select your DFS connector from the grid. Use the search field to filter by name.
Step 3: Fill in the Connection Properties (a Connection Name that other datastores can reuse later, the storage location and Authentication fields, and optionally Secrets Management to retrieve credentials from a secrets manager), the Datastores Extraction field, and the Datastore Properties described in the Field reference. Then click Test connection.
Step 4: A success message confirms that the connection has been verified. Click Finish to create the datastore.
Info
The Finish and Next buttons stay disabled until the connection test passes on the current values. If you change a connection field after a successful test, test again. If the test fails, check the connector's troubleshooting page.
Tip
To link an enrichment datastore so Qualytics can store anomalies and metadata from the first operation, click Next instead of Finish. See Link Enrichment on Datastore Creation.
Step 5: A success dialog confirms that your datastore has been added. Click Go to your datastore to open its page.
