Databases are optimized for durable storage: transactions, constraints, consistency, recovery. Amazon OpenSearch Service is optimized for a different job: language-aware search (matching, synonyms, typo tolerance, relevance ranking), deep vector capabilities for hybrid search that combines lexical matching with semantic similarity, and sub-second analytics at scale. Both store data reliably. But each excels at what the other merely tolerates. If your application needs both great transactional writes and great search, you run both. Amazon OpenSearch Ingestion and its zero-ETL integrations now keep them in sync automatically.
The hard part has always been the sync. Your product catalog lives in PostgreSQL. Your session data lives in DynamoDB. Your search experience lives in OpenSearch Service. A customer updates their address, a product goes out of stock, a price changes. That change needs to appear in search results within seconds. Continuously. Without a fragile pipeline that breaks when someone alters a column. OpenSearch Ingestion eliminates that pipeline entirely for Amazon Aurora (Aurora), Amazon RDS (RDS), and Amazon DynamoDB (DynamoDB), with native change data capture and near-real-time synchronization out of the box.
