> For the complete documentation index, see [llms.txt](https://upsolver.gitbook.io/content/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://upsolver.gitbook.io/content/how-to-guides-1/connectors/create-connections.md).

# Create Connections

Before creating your data pipeline with Upsolver, ensure that you have the necessary connectors in place to support your intended use case.

For data ingestion, you first need a connection to your data source; then, in order to read your data into a staging table, you should have a connection to a metadata store, along with a corresponding cloud storage location. 

After your data has been ingested and transformed, you need a connection to your target location for outputting your data.

{% hint style="success" %}
If you have deployed Upsolver on AWS, you will have an Amazon S3 and AWS Glue Data Catalog connection created by default.

See the guide to [Deploy Upsolver on AWS](/content/how-to-guides-1/setup/deploy-upsolver-on-aws.md) for more information.
{% endhint %}

Connections determine the credentials that Upsolver uses to read and/or write your data, so you may want to explicitly create your own Amazon S3 or AWS Glue Data Catalog connections to configure specific permissions.

{% hint style="warning" %}
The use of static IAM credentials for cross-account access is deprecated and Upsolver recommends that you use an IAM role instead.
{% endhint %}

#### Learn more about a connection type:

* [Amazon Kinesis](/content/how-to-guides-1/connectors/create-connections/amazon-kinesis.md)
* [Amazon Redshift](/content/how-to-guides-1/connectors/create-connections/amazon-redshift.md)
* [Amazon S3](/content/how-to-guides-1/connectors/create-connections/amazon-s3.md)
* [Apache Kafka](/content/how-to-guides-1/connectors/create-connections/apache-kafka.md)
* [AWS Glue Data Catalog](/content/how-to-guides-1/connectors/create-connections/aws-glue-data-catalog.md)
* [ClickHouse](/content/how-to-guides-1/connectors/create-connections/clickhouse.md)
* [Confluent Kafka](/content/how-to-guides-1/connectors/create-connections/confluent-cloud.md)
* [Elasticsearch](/content/how-to-guides-1/connectors/create-connections/elasticsearch.md)
* [Microsoft SQL Server](/content/how-to-guides-1/connectors/create-connections/microsoft-sql-server.md)
* [MongoDB](/content/how-to-guides-1/connectors/create-connections/mongodb.md)
* [MySQL](/content/how-to-guides-1/connectors/create-connections/mysql.md)
* [PostgreSQL](/content/how-to-guides-1/connectors/create-connections/postgresql.md)
* [Snowflake](/content/how-to-guides-1/connectors/create-connections/snowflake.md)
* [Tabular](/content/how-to-guides-1/connectors/create-connections/tabular.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://upsolver.gitbook.io/content/how-to-guides-1/connectors/create-connections.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.