Zero ETL RDS Oracle
In this show we explore Amazon RDS for Oracle zero-ETL integration with Amazon Redshift and how it enables near real-time analytics and machine learning (ML) to analyze petabytes of transactional data in Amazon Redshift without complex data pipelines for extract-transform-load (ETL) operations. The show will also include demo in the 2nd half where we build the integration.
In this episode, we explore zero-ETL integration between Amazon RDS for Oracle and Amazon Redshift. The experts explain how zero-ETL eliminates the need for complex data pipelines by automatically replicating data from transactional databases to data warehouses in near real-time (within seconds). They demonstrate how to set up the integration, highlighting that no coding is required - just configuration of source and target databases with include/exclude patterns for schemas and tables. The team discusses practical use cases, such as consolidating data from multiple OLTP sources for reporting and analytics, while addressing important considerations like performance impact, monitoring capabilities, and current limitations.
Key Highlights
- What is Zero-ETL: A fully managed AWS integration service that automatically replicates data from RDS databases (Oracle, MySQL, PostgreSQL) to Amazon Redshift without writing ETL code.
- Near Real-Time Replication: Data changes are replicated within seconds after transactions commit, following an initial one-time data copy.
- Filtering Capabilities: Currently supports database and schema-level filtering with table-level include/exclude patterns; column and row-level filtering not yet available.
- Cross-Account Support: Source and target databases can reside in different AWS accounts
- Cost Structure: No additional fees for zero-ETL integration itself; only pay for existing resources used for processing.
- Use Cases: Ideal for aggregating multiple OLTP sources into a central data warehouse for reporting, dashboards, and analytics without maintaining complex ETL pipelines.
- Performance Considerations: Uses Change Data Capture (CDC) from transaction logs after initial copy; minimal impact on source database performance.
Hosts of the show
Guest
🎤 Prasad Matkar - Sr Database Specialist Solutions Architect @ AWS
🎤 Vetrivel Subramani - Sr Database Specialist Solutions Architect @ AWS
Links from today's episode
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