AWS DynamoDB and Google BigQuery integration

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

Get Started See n8n in action

How to connect AWS DynamoDB 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.

Build your own AWS DynamoDB and Google BigQuery integration

Create custom AWS DynamoDB 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 DynamoDB and Google BigQuery integration details

AWS DynamoDB

AWS DynamoDB is an efficient NoSQL database, capable of running high-performance applications. It is utilized to develop software applications, create media metadata stores, deliver seamless retail experiences, and even scale gaming platforms.

AWS DynamoDB node docs + examples

AWS DynamoDB credential docs

See AWS DynamoDB integrations

Related categories

Data & Storage 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 DynamoDB

Other integrations with Google BigQuery

Save engineering resources

Reduce time spent on customer integrations, engineer faster POCs, keep your customer-specific functionality separate from product all without having to code.

Learn more

FAQs