RDBMS and Apache Geode Data Movement - Heather Riddle & Paul Warren, HCSC

December 14, 2017
Extract, transform, load (ETL) has always been complex and expensive for moving massive data sets from one data source to another. This is especially true if the source system is a traditional RDBMS with complicated relationships between tables. Most of the time, traditional ETL processes are implemented with batch, monolithic, and tightly coupled approaches. As the result, traditional ETL processes are often considered fragile, hard to maintain, not easy to tune, and often introduce high data latency between source and destination systems. In this session, Paul and Heather will cover how to create cloud-native event driven microservices (ETL pipeline) for RDBMS and Apache Geode by using Cloud Foundry, Spring Cloud Stream, and RabbitMQ/Kafka. The pipelines can handle high volume data sets and complex database queries, yet with low data latency between the source RDBMS and Apache Geode. In addition, the design is highly tunable and scalable. The session will also cover analysis of performance metrics based on the implementations of real world use cases. Slides: TBA Paul Warren, Senior Engineer, HCSC Heather Riddle, Senior Engineer, HCSC Filmed at SpringOne Platform 2017
Previous
Tried and True Approach to Cloud Native Design - Rahul Kandhari, HCL
Tried and True Approach to Cloud Native Design - Rahul Kandhari, HCL

The session will be discussing HCL’s experience from creating our own microservices. It will discuss HCL’s ...

Next Video
Managing the Complexity of Microservices Deployments - Prithpal Bhogill, Kenny Bastani
Managing the Complexity of Microservices Deployments - Prithpal Bhogill, Kenny Bastani

To rapidly deliver microservices to production, organizations are turning to infrastructure automation prov...

SpringOne Platform 2019 Presentations

Watch Now