Connect Google Bigquery and Cassandra to Build Intelligent Automations
Enable Integrations or automations with these events of Google Bigquery and Cassandra
Enable Integrations or automations with these events of Google Bigquery and Cassandra
Actions
Delete Rows
Deletes rows from a BigQuery table that match the provided WHERE condition.
Run SQL query
Run a SQL query and return results.
Find Row
Find row(s) by specifying a table, a WHERE clause, an optional ORDER BY, and a LIMIT.
Insert Rows
Insert one or more rows into a BigQuery table.
Update Rows
Update specified fields in rows of a BigQuery table that match the provided WHERE condition.
Create a Table
Creates a new, empty table in the dataset.
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Frequently Asked Questions
To start, connect both your Google Bigquery and Cassandra accounts to viaSocket. Once connected, you can set up a workflow where an event in Google Bigquery triggers actions in Cassandra (or vice versa).
Absolutely. You can customize how Google Bigquery data is recorded in Cassandra. This includes choosing which data fields go into which fields of Cassandra, setting up custom formats, and filtering out unwanted information.
The data sync between Google Bigquery and Cassandra typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Google Bigquery and Cassandra. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Google Bigquery
BigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your data analysts productive.
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About Cassandra
Apache Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.
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