How to load data from Pinterest to Postgres destination

Learn how to use Airbyte to synchronize your Pinterest data into Postgres destination within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Pinterest connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Postgres destination for your extracted Pinterest data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Pinterest to Postgres destination in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync to Manually

Step 1: Set Up Pinterest Developer Account

To access Pinterest Ads data, start by setting up a Pinterest Developer account. Visit the Pinterest Developers website, create an account, and set up a new app. This will give you access to the Pinterest API, which you can use to programmatically extract data.

Once your developer account and app are set up, generate an API access token. This token will authenticate your requests to the Pinterest API. Ensure you request the necessary permissions to access ads-related data.

Familiarize yourself with the Pinterest Ads API documentation, focusing on the endpoints related to the data you want to extract. Common endpoints include those for campaigns, ad groups, and ads metrics. Understand the required parameters and structure of requests and responses.

Develop a script using a programming language of your choice (e.g., Python, JavaScript) to make HTTP requests to the Pinterest Ads API. Use the access token to authenticate these requests. Parse the JSON response to extract relevant data fields. Store this data temporarily in a format suitable for loading into PostgreSQL, such as CSV or JSON files.

Ensure your PostgreSQL database is set up and running. Create a new database or use an existing one, and define the schema that will store the Pinterest Ads data. Create tables with columns that match the fields extracted from the Pinterest API.

Use SQL commands or a database client to load the extracted data into PostgreSQL. If using a script, you can leverage libraries like psycopg2 (for Python) to programmatically insert data into the database. Ensure the data types in PostgreSQL match those of the incoming data.

Set up a cron job or a similar scheduling tool to automate the data extraction and loading process. This will ensure your PostgreSQL database is regularly updated with the latest data from Pinterest Ads. Adjust the frequency based on your data needs and API rate limits.

By following these steps, you can effectively move data from Pinterest Ads to a PostgreSQL database without the need for third-party connectors or integrations.