AWS SES and Google BigQuery connection

Save yourself the work of writing custom integrations for AWS SES and Google BigQuery and use n8n instead. Build adaptable and scalable Communication, Development, workflows that work with your technology stack. All within a building experience you will love.

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Ways to connect AWS SES and Google BigQuery

Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Create your own AWS SES and Google BigQuery connection

Create custom AWS SES and Google BigQuery workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

AWS SES supported actions

Google BigQuery supported actions

AWS SES and Google BigQuery connection details

AWS SES

With Amazon SES (Simple Email Service), you do not have to use an on-premises Simple Mail Transfer Protocol (SMTP) system. It is a reliable, scalable email that helps you reach out to and communicate with your audience and customers efficiently, and at the lowest prices.

AWS SES node docs + examples

AWS SES credential docs

See AWS SES integrations

Related categories

Communication Development

Google BigQuery

Many businesses use the Google Cloud service BigQuery for data reporting. BigQuery is categorized as an Advanced Data Connector. The amount of data that needs to be processed could be quite large (up to 10,000 columns and tens of millions of rows).

Google BigQuery node docs + examples

Google BigQuery credential docs

See Google BigQuery integrations

Related categories

Data & Storage Development

Other integrations with AWS SES

Other integrations with Google BigQuery

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