Building a Scalable Search Architecture | Confluent

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This post details building a scalable search architecture using Kafka Connect with JDBC Source and Elasticsearch Sink connectors. It explains the challenges of using RDBMS for search, introduces Kafka as a middleware for scalability and flexibility, and outlines two Kafka Connect-based approaches for indexing pipelines. The JDBC connector section covers its modes of operation (incrementing, timestamp, combination, custom query, bulk import) and schema evolution with Schema Registry. The Elasticsearch connector section provides a basic configuration for indexing data from Kafka to Elasticsearch. It also discusses the importance of considering query performance for the JDBC connector and mapping strategies for Elasticsearch.