A company has a gaming application that stores data in Amazon DynamoDB tables. A data engineer needs to ingest the game data into an Amazon OpenSearch Service cluster. Data updates must occur in…

Question

Options

• AUse AWS Step Functions to periodically export data from the Amazon DynamoDB tables to an
• BConfigure an AWS Glue job to have a source of Amazon DynamoDB and a destination of
• CUse Amazon DynamoDB Streams to capture table changes. Use an AWS Lambda function to
• DUse a custom OpenSearch plugin to sync data from the Amazon DynamoDB tables.

• A
  10% (5)
• B
  4% (2)
• C
  73% (36)
• D
  12% (6)

Explanation

DynamoDB Streams can capture changes to items in DynamoDB tables (such as inserts, updates, and deletes) in near real-time. An AWS Lambda function can be triggered by these streams, and the function can process the changes and update the data in Amazon OpenSearch Service. This solution meets the requirement for near real-time updates with minimal latency. The "Use AWS Step Functions to periodically export data from the Amazon DynamoDB tables to an Amazon S3 bucket. Use an AWS Lambda function to load the data into Amazon OpenSearch Service." solution involves exporting data periodically, which does not meet the requirement for near real- time updates. Periodic exports could introduce delays. AWS Glue is generally used for batch processing, and it is not designed for near real-time data ingestion. It would not be an ideal solution for real-time or low-latency requirements. The "Use a custom OpenSearch plugin to sync data from the Amazon DynamoDB tables." option suggests building a custom solution, which would involve significant development effort. Moreover, OpenSearch does not natively support such plugins, making this solution less practical compared to using DynamoDB Streams and Lambda, which are designed to work together.

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