Overview: Integrations
In this section, we will explore Integrations (opens in a new tab), an essential element of data mapping required to process Data Subject Requests (DSRs).
What are integrations?
An Integration connects Fides to your databases and third-party SaaS applications, allowing Fides to execute privacy requests against all data in your organization.
Currently, Fides offers supported integrations for commonly used databases such as PostgreSQL, BigQuery, and Snowflake, as well as popular SaaS applications including Hubspot and Google Analytics, among many others! To view the list of currently supported vendors, please refer to the Supported integrations section below.
We're constantly adding new integrations and you can request additional integrations from your customer support team!
How to manage integrations
This guide will get you started quickly with integrating your systems:
1. Identify the system you want to integrate with
We support many common databases and third-party SaaS applications and we're always adding more! If you don't see the vendor that you need, you can request additional integrations from your customer support team or, even, build a custom integration (tutorial coming soon!).
2. Collect the information that you will need to connect to the system
For each vendor, you'll need to provide unique connection credentials. Our vendor guides, linked below, outline the information you need to collect, making it easier to gather the required credentials and set up the connections.
3. Configure the connection information and test the integration
We recommend using the UI to fill in the connection information you collected in Step 3 and test the integration. For detailed steps, please see our guide for Managing integrations using the UI.
4. Configure the dataset
If you are connecting to a database, you will need to generate and link dataset in order to process Data Subject Requests (DSRs). For detailed steps, please see our guide for Linking datasets.
Supported integrations
Supported databases
Amazon DynamoDB | Amazon Redshift | Google BigQuery |
---|---|---|
MariaDB | MongoDB | Microsoft SQL Server |
MySQL | PostgreSQL | Redshift |
Snowflake |