Building search experiences for JSON data with Amazon OpenSearch Service

Amazon OpenSearch Service can serve as a dedicated discovery layer on top of operational data stores like DynamoDB, DocumentDB, and Aurora, combining full-text, vector, and geospatial search in a single JSON query. Using a restaurant discovery app as a working example, the post covers index mapping strategies (per-field indexing, nested objects, knn_vector for embeddings), text analysis with English analyzers and synonym expansion, HNSW-based vector search for semantic matching, geo_point-based proximity filtering, and hybrid queries that merge all three modalities. It also covers CDC-based ingestion via OpenSearch Ingestion, common mapping pitfalls, and when to keep data in source stores versus syncing to OpenSearch.

Source: https://aws.amazon.com/blogs/database/building-search-experiences-for-json-data-with-amazon-opensearch-service. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.