A gaming application stores events in Amazon DynamoDB and a data engineer must ingest that data into Amazon OpenSearch Service with near-real-time updates. Which solution meets this requirement?
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Correct answer: Use Amazon DynamoDB Streams to capture table changes. Use an AWS Lambda function to process the stream and update Amazon OpenSearch Service..
Why this is the answer
This solution is optimal because DynamoDB Streams provide a time-ordered sequence of item-level modifications in a DynamoDB table, enabling near-real-time data capture. An AWS Lambda function can then be triggered by these stream events to process the changes and update the Amazon OpenSearch Service cluster. This architecture ensures low latency and efficient synchronization. Periodically exporting data via Step Functions and S3 introduces significant latency, failing the "near-real-time" requirement. AWS Glue jobs are suitable for batch processing and ETL, but not designed for continuous, near-real-time synchronization from DynamoDB to OpenSearch. Custom OpenSearch plugins are generally not recommended for this type of data ingestion and synchronization task due to complexity, maintenance, and potential security concerns, and there isn't a standard plugin for direct DynamoDB integration.
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