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You are tasked with implementing a data transformation service that can handle both batch and real-time data processing. Which AWS service would you recommend, and what are the key considerations for designing a hybrid data processing architecture?
You are tasked with implementing a data transformation service that can handle both batch and real-time data processing. Which AWS service would you recommend, and what are the key considerations for designing a hybrid data processing architecture?
Explanation:
Option C is the most suitable choice for this scenario. AWS Glue is a fully managed ETL service that can handle both batch and real-time data processing. By using Glue jobs, you can perform batch data processing tasks, while Glue triggers can be used to automate real-time data processing workflows. When designing a hybrid data processing architecture, consider factors such as data source integration, data format compatibility, transformation logic, fault tolerance, and scalability. You should also consider the cost implications of using both batch and real-time processing and choose the appropriate Glue pricing model, such as on-demand or reserved capacity, based on your workload requirements.