MySQL CDC to BigQuery: Binlog-based capture addresses limitations of periodic syncs

Limitations of Periodic Syncs

Traditional MySQL-to-warehouse pipelines often rely on scheduled jobs that select rows and compare them to previous states. This method, however, fails to detect rows that were deleted between syncs and cannot capture intermediate states of rows that changed multiple times. Additionally, these periodic scans can impose a significant load on the production database, especially for large tables.

How Binlog-based Change Data Capture Works

Change Data Capture (CDC) offers a more reliable alternative by reading directly from MySQL's binary log (binlog). The binlog is an internal mechanism MySQL uses for replication, recording every INSERT, UPDATE, and DELETE operation in order, along with the complete row state. This approach ensures that all changes are captured without inference or dependence on batch job schedules, providing a more complete and accurate data stream.

MySQL Prerequisites for CDC

Implementing binlog-based CDC requires specific MySQL configurations. Binary logging must be enabled in ROW format with FULL row images, ensuring that DELETE and UPDATE events include the complete before/after state. The binlog_row_value_options must not be set to PARTIAL_JSON, as this would only log partial updates for JSON columns. The replication user needs REPLICATION SLAVE, REPLICATION CLIENT, SELECT, RELOAD, and SHOW DATABASES privileges. Each CDC connection also requires a unique server-id to prevent collisions with existing replicas. Finally, binlog retention must be long enough to cover potential downtime, allowing the CDC connection to resume from where it left off.