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Easy Google BigQuery to IBM DB2 Data Warehouse integration with RudderStack
RudderStack’s open source Reverse ETL connection allows you to integrate RudderStack with your Google BigQuery Data Warehouse to track event data and automatically send it to IBM DB2 Data Warehouse. With the RudderStack Reverse ETL connection, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.
Popular ways to use IBM DB2 Data Warehouse
Automatic schema creation
Simplify your workflow with predefined schemas, automatically created for you in your IBM DB2 Data Warehouse warehouse.
Sync data faster
Leverage best in class sync times and load data to IBM DB2 Data Warehouse every 30 minutes (or even faster!).
Customize data loads
Customize data and loads for IBM DB2 Data Warehouse across multiple databases and schemas.
Frequently Asked Questions
How do you integrate your Google BigQuery data warehouse with IBM DB2 Data Warehouse?
With Rudderstack, integration between Google BigQuery source and IBM DB2 Data Warehouse is simple. Set up a Google BigQuery source source and start sending data.
Is it expensive to integrate Google BigQuery source with IBM DB2 Data Warehouse?
How long does it take to integrate Google BigQuery source with IBM DB2 Data Warehouse?
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery source and IBM DB2 Data Warehouse.
RudderStack Google BigQuery Documentation
Refer to our step-by-step guide and start using Google BigQuery today
About IBM DB2 Data Warehouse
IBM DB2 is a highly flexible data warehousing solution, ideal for private clouds and containerized app deployments. With its elastic scaling and fast querying capabilities, DB2 is ideal for operational analytics needs. With DB2, you have the perfect data warehouse to modernize your data management.
About Google BigQuery
Google BigQuery is a fully-managed cloud data warehouse that allows you to store and analyze petabytes of data in no time. It is serverless, highly scalable, and cost-effective and is designed for businesses to analyze massive datasets and make informed business decisions. Google BigQuery also allows running complex analytical SQL-based queries using built-in machine learning capabilities.