Deploying Elasticsearch alongside relational databases like MySQL can enhance search capabilities, but it requires synchronization of data between systems. This blog post explains how to use Logstash with its JDBC input plugin to efficiently synchronize data from a MySQL database to Elasticsearch. The process involves configuring Logstash to periodically poll MySQL for records that have been inserted or updated since the last check, using fields like "modification_time" to track changes. By setting Elasticsearch's "_id" field to match the MySQL "id" field, direct mapping is achieved, and updates in MySQL overwrite corresponding documents in Elasticsearch efficiently. The approach resolves common synchronization issues by incorporating conditions like "modification_time < NOW()" in SQL queries to ensure each record is sent to Elasticsearch only once, avoiding data loss or redundancy. The synchronization setup requires specific configurations in MySQL and Logstash, and while it efficiently handles insertions and updates, deletion synchronization needs additional strategies such as soft deletes or dual-system commands. The outlined methods are tested with MySQL but are applicable to any RDBMS, offering a robust solution for maintaining consistency between MySQL and Elasticsearch.