Connect Redshift to BigQuery
Send Redshift table or view and custom SQL to BigQuery on a schedule. Refresh as often as every 15 minutes.
BigQuery
dataset redshift
table_or_viewcustom_sql
How to connect Redshift and BigQuery
4 steps. You can preview the Redshift data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect Redshift
Add the Redshift account you want to export from.
Connect Redshift
Step 2 of 4
Choose what to export
Pick the Redshift data you want in BigQuery.
Step 3 of 4
Connect BigQuery
Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the Redshift data.
Step 4 of 4
Choose a write mode and schedule
Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.
Each run overwrites table_or_view with fresh Redshift data.
Coupler.io made it easy to create dashboards and reports from different data sources. The sync is reliable and the user experience is amazing.
Take your data analytics to the next level
Sign Up with Google
Sign Up with MICROSOFT
SIGN UP WITH EMAIL
By signing up to Coupler.io, you agree to our Privacy Policy and Terms of Use.
Build your Redshift integrations with these destinations
Get the most of Redshift to BigQuery integration
Gather data
Understand data
Automate data
Act on data
2 report types, including Table or view and Custom SQL.
Yes. SQL query lets you write a query instead of picking a ready-made report type.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with Redshift data.
Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example Google Sheets or Airtable, and join or append them before the data reaches BigQuery.
