Integrate Jekyll with Google BigQuery
Don't go through the pain of direct integration. RudderStack’s Jekyll integration makes it easy to send data from Jekyll to Google BigQuery and all of your other cloud tools.
Easy Jekyll to Google BigQuery integration with RudderStack
RudderStack’s open source Jekyll integration allows you to integrate RudderStack with your Jekyll to track event data and automatically send it to Google BigQuery. With the RudderStack Jekyll integration, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.
Popular ways to use Google BigQuery and RudderStack
Simplify your workflow with predefined schemas, automatically created for you in your Google BigQuery warehouse.
Leverage best in class sync times and load data to Google BigQuery every 30 minutes (or even faster!).
Customize data and loads for Google BigQuery across multiple databases and schemas.
Frequently Asked Questions
With Rudderstack, integration between Jekyll and Google BigQuery is simple. Set up a Jekyll source and start sending data.
Timing can vary based on your tech stack and the complexity of your data needs for Jekyll and Google BigQuery.
Yes, RudderStack streamlines the integration and management of your connection between Jekyll & Google BigQuery, but you check out our guide on How to load data from PostgreSQL to Google BigQuery to learn how to connect the tools manually.
About Google BigQuery
Google BigQuery is an industry-leading fully-managed cloud data warehouse that allows you to store and analyze petabytes of data in no time and leverage Google’s machine learning features. RudderStack lets you add Google BigQuery as a destination where you can send your customer event data and params from the data source of your choice., without the pain of detailed setup or custom pipeline development. Setting up a pipeline to BigQuery cloud storage requires a significant amount of detailed engineering work, dealing with googleapis, config files, commands like createdataset and create table and more. With RudderStack, you simply need to set up a service account for authentication in Google Cloud Platform, ensure your IAM profile has the correct permissions and then specify the required details (like projectid). From there, RudderStack will take care of sending data directly to GCP (google-cloud/bigquery), including metadata, without you having to manage a cloud client library, set up a new git workflow in your command line or spend engineering cycles trying to optimize loads. In fact, with RudderStack’s streaming integrations you can even send data to Google in real-time. If you have multiple databases, RudderStack also allows you to send data to relational databases like PostgreSQL, SQL server, mySQL and more.