Huolala’s Real‑Time Data Synchronization with Flink CDC: Architecture, Practices, and Future Outlook

Huolala, a logistics platform founded in 2013, processes petabyte‑scale daily data from millions of drivers and users across 11 markets, requiring a stable, low‑latency pipeline to capture and analyze operational data.

Facing severe latency and stability issues with the legacy Canal solution, Huolala evaluated alternatives using a four‑quadrant framework and chose Flink CDC for its functional completeness, Canal compatibility, link stability, and data‑consistency guarantees.

A comparative analysis of open‑source CDC tools (Flink CDC, Canal, Apache SeaTunnel, DataX) highlighted Flink CDC’s unique support for full‑plus‑incremental sync, distributed deployment, and robust HA mechanisms, leading to an 80‑fold reduction in data‑capture latency.

In production, the FeiLiu real‑time computing platform was extended to integrate Flink CDC, adding metrics, configurable catalogs, enhanced data protocols, SDK wrappers, schema‑change handling, and multi‑threaded parsing, while also implementing throttling and global lineage tracking for stability.

Data validation combines conventional log checks, statistical batch comparisons, data‑science‑driven analyses, and dual‑run verification to ensure end‑to‑end consistency between source databases and downstream warehouses.

Future work focuses on coupling Flink CDC with lake‑house formats (Paimon, Iceberg) via the Fluss project and Apache Amoro, automating data‑lake ingestion, supporting multi‑source subscriptions (e.g., MongoDB), and further optimizing storage compaction and query performance.