Implementing search on Amazon DynamoDB data using zero-ETL integration with Amazon OpenSearch service

This article explains how to implement advanced search capabilities on Amazon DynamoDB data using zero-ETL integration with Amazon OpenSearch Service, eliminating the need for custom data pipelines.

• Zero-ETL integration syncs DynamoDB data to OpenSearch via PITR exports and DynamoDB Streams
• Supports multi-field search across product names, descriptions, categories, and tags simultaneously
• Enables multi-range filtering by price, ratings, categories, and other product attributes
• Provides faceted browsing with aggregations for discovery and progressive result refinement
• Implements fuzzy search and autocomplete to handle typos and spelling mistakes
• Enables semantic search using vector embeddings via Amazon Bedrock Titan models
• Solution uses OpenSearch Ingestion pipelines to transform and sync data near real-time
• Includes step-by-step implementation guide with DynamoDB table setup, OpenSearch domain creation, and pipeline configuration
• Recommends monitoring pipeline health, enabling DLQs, encryption, and least-privilege IAM access
• Cost considerations include DynamoDB Streams charges, OpenSearch cluster costs, and Bedrock token usage

The integration allows e-commerce applications to maintain transactional consistency in DynamoDB while leveraging OpenSearch's powerful search and analytics capabilities without building custom ETL pipelines.