Source: Skip the heavy lifting: Moving Redshift to BigQuery easily from Google Cloud
Enterprise data warehouses are getting more expensive to maintain. Traditional data warehouses are hard to scale and often involve lots of data silos. Business teams need data insights quickly, but technology teams have to grapple with managing and providing that data using old tools that aren’t keeping up with demand. Increasingly, enterprises are migrating their data warehouses to the cloud to take advantage of the speed, scalability, and access to advanced analytics it offers.
With this in mind, we introduced the BigQuery Data Transfer Service to automate data movement to BigQuery, so you can lay the foundation for a cloud data warehouse without writing a single line of code. Earlier this year, we added the capability to move data and schema from Teradata and S3 to BigQuery via the BigQuery Data Transfer Service. To help you take advantage of the scalability of BigQuery, we’ve now added a service to transfer data from Amazon Redshift, in beta, to that list.
Data and schema migration from Redshift to BigQuery is provided by a combination of the BigQuery Data Transfer Service and a special migration agent running on Google Kubernetes Engine (GKE), and can be performed via UI, CLI or API. In the UI, Redshift to BigQuery migration can be initiated from BigQuery Data Transfer Service by choosing Redshift as a source.
The migration process has three steps:
You can see more here about how customers are using the BigQuery Data Transfer Service to move database instances easily.
To get started, follow our step-by-step guide, or read our article on migrating data to BigQuery using Informatica Intelligent Cloud Services. Qualifying customers can also take advantage of our data warehouse migration offer, which provides architecture and design guidance from Google Cloud engineers, proof-of-concept funding, free training, and usage credits to help speed up your modernization process. Learn more here.