PostgreSQL

PostgreSQL is an open-source relational database that stores data in tables (rows and columns) and you use SQL (Structured Query Language) to read and write data.

Prerequisite

Ensure the following requirements are met before you connect PostGreSQL as a data sourcee:

• A PostgreSQL instance you can connect to (host, port, credentials).
• The name(s) of the schema(s) you want to monitor. A schema in PostgreSQL is like a namespace to group tables.
• Access rights: the username/password used should have reading privileges on those schemas.
• If you want query-analysis, ensure the PostgreSQL environment captures query logs or has necessary permissions.
• For integration with ADOC, a Data Plane ready (either preexisting or newly created).

Add PostGreSQL as a Data Source

Step 1: Start Setup

1. Select Register from the left main menu.

2. Select Add Data Source > Azure Data Lake from the list of data sources.

3. On the Data Source Details page:

   1. Name the data source.
   2. Add a short description (optional).
   3. Ensure the Data Reliability toggle is enabled and select your data plane from the dropdown.

4. Select Next.

Step 2: Add Connection Details

1. Enter PostgreSQL connection details:

   1. PostGreSQL URL (host, port, database)
   2. Username
   3. Password

2. Click Test Connection to validate access. If your credentials are valid, you receive a Connected message. If you get an error message, validate the PostgreSQL credentials you entered.

3. Click Next.

Step 3: Set Up Observability

In the Observability Set Up page, perform the following:

1. Turn on Query Analysis Service (named “Torch Query Analysis Service” in UI) if you want insight into query performance.
2. Specify which schema(s) to monitor. You can add more than one schema.
3. Select the PostgreSQL Environment — e.g. dev, staging, production.
4. Optionally enable Crawler Execution Schedule: set up when (time, time zone) the crawler should run automatically.
5. Click Submit.

After this, PostgreSQL is added as a data source. You can choose to run the crawler right away or run on schedule.

After Setup

Once PostgreSQL is connected and crawling is complete:

• A card for this PostgreSQL source will appear on the Register page. This card shows basics like:

  • The monthly cost incurred so far (if applicable)
  • Status of the crawler (running / scheduled / error)
  • Other metadata (e.g. when it was last crawled)

• In Data Reliability > Discover Assets, you can see assets (schemas, tables) from your monitored schemas.

• Query performance metrics, if query analysis is enabled — e.g. which queries are expensive or which tables are accessed most.

What’s Next

• Once basic monitoring is working, explore setting up alerts in ADOC — so you get notified if data quality drops or queries misbehave.
• Use the lineage or data flow capabilities (if available) to see how tables/tables are related or how data moves among tables.
• Periodically review schemas included and remove ones no longer needed.
• Use the insights from query analysis & schemata changes to tune database performance: e.g. add indexes, rewrite queries, or archive old data.