Design patterns for implementing Hive Metastore for Amazon EMR on EKS

This article discusses design patterns for implementing Hive Metastore (HMS) in Amazon EMR on EKS, exploring three architectural approaches for metadata management in big data environments:

• HMS as a sidecar container: Simple setup where HMS runs in the same pod as the data processing framework, ideal for small-scale deployments
• Cluster dedicated HMS: HMS runs in multiple pods within the same EKS cluster, providing moderate isolation and resource efficiency
• External HMS: HMS deployed in a separate EKS cluster, offering maximum isolation and centralized metadata management across multiple data processing clusters

Key benefits of these patterns include: • Flexible metadata management • Independent scaling of metadata services • Support for various data processing frameworks like Apache Spark • Enhanced security and isolation options

The article provides detailed implementation guidance, including configuration steps, job submission processes, and best practices for each architectural pattern.