Data modeling for microservices with Cassandra and Spark
Jeff Carpenter describes how data modeling can be a key enabler of microservice architectures for transactional and analytics systems, including service identification, schema design, and event streaming.
|Talk Title||Data modeling for microservices with Cassandra and Spark|
|Conference||Strata + Hadoop World|
|Conf Tag||Make Data Work|
|Location||New York, New York|
|Date||September 27-29, 2016|
Choice Hotels International is in the midst of a multiyear transformation that is changing key elements of its IT enterprise—replacing its monolithic central reservation system with a cloud-based, microservice-style architecture using Cassandra as the backend. A parallel project is replacing its enterprise data warehouse and reporting systems with an advanced analytics platform based on Spark and Kafka. Jeff Carpenter describes the key role that data modeling played in helping to define the architectures of these new systems. Along the way, Jeff highlights several of the challenges Choice Hotels faced, including achieving transactional behavior across distributed services, accessing historical data from online systems, and maintaining an extensible data design when new features are added. Topics include: