Connect Rocket.chat to BigQuery
Send Rocket.chat subscriptions, users, teams and 3 more data types to BigQuery on a schedule. Refresh as often as every 15 minutes.
BigQuery
dataset rocket_chat
subscriptionsusersteamsroomschannels- 1 more data type
How to connect Rocket.chat and BigQuery
4 steps. You can preview the Rocket.chat data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect Rocket.chat
Enter your Rocket.chat endpoint URL, API token and user ID. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the Rocket.chat 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 Rocket.chat 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 subscriptions with fresh Rocket.chat data.
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6 data types, including Subscriptions, Users, Teams, Rooms and Channels.
With your Rocket.chat endpoint URL, API token and user ID, entered once when you add the connection.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with Rocket.chat 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 100ms or Amazon Seller Central, and join or append them before the data reaches BigQuery.
