# Overview

**Aporia monitors your models by connecting *****directly***** to your data.** If you don't store your predictions yet, see our guide on [Storing Your Predictions](/storing-your-predictions/overview.md).

Aporia currently supports the following data sources:

* Amazon S3
* Athena
* BigQuery
* Databricks
* Glue Data Catalog
* Google Cloud Storage
* PostgreSQL
* Redshift
* Snowflake
* Azure Blob Storage
* MSSQL

{% hint style="info" %}
If your storage or database are not shown here, please contact your Aporia account manager for further assistance.
{% endhint %}

### Configure Data Source

Connecting to a data source begins with configuring its connection details. For example, to connect to a Postgres database, we can create a data source using the following details:

```python
url="jdbc:postgresql://<POSTGRES_HOSTNAME>/<DBNAME>",
user="<DB_USER>",
password="<DB_PASSWORD>"
```

{% hint style="info" %}
Please refer to the documentation page of the relevant data source for a complete list of requirements and configuration options.
{% endhint %}

### Link Your Data

After creating a data source, we can create a model version and link our data. This process consist of two steps:

1. **Linking a dataset** - define a query to retrieve your data.
2. **Mapping model schema** - map your model's raw inputs, features, predictions, and actuals. The fields you can map are from the columns you retrieved.

The ground truth can be `NULL` until it actually has value, that's okay.

### You are good to go, it's time to get value! :tada:


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aporia.com/data-sources/overview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.