Connect Oracle Database and amazon redshift to Build Intelligent Automations
Enable Integrations or automations with these events of Oracle Database and amazon redshift
Enable Integrations or automations with these events of Oracle Database and amazon redshift
Actions
Execute a query
Execute a query on Oracle Database
Insert a Row
Insert a row in Oracle Database table
Create or Update
Create or Update a row in Oracle Database table
Update a row
Update a row in Oracle Database table
Find row
Find row via Custom Query
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Frequently Asked Questions
To start, connect both your Oracle Database and amazon redshift accounts to viaSocket. Once connected, you can set up a workflow where an event in Oracle Database triggers actions in amazon redshift (or vice versa).
Absolutely. You can customize how Oracle Database data is recorded in amazon redshift. This includes choosing which data fields go into which fields of amazon redshift, setting up custom formats, and filtering out unwanted information.
The data sync between Oracle Database and amazon redshift 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 Oracle Database and amazon redshift. 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 Oracle Database
Oracle Database is a multi-model database management system produced and marketed by Oracle Corporation. It is designed to store and retrieve large amounts of data, providing high performance, scalability, and reliability for enterprise applications. Oracle Database supports SQL as a query language and offers features such as data warehousing, online transaction processing, and data security.
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About amazon redshift
Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake.
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