Through years of IT development, the bank has achieved comprehensive business and management informatization. To enhance technical support for operations, it required an upgrade to its unified query system.

Ensure low-latency data transmission from core systems and deliver high-concurrency real-time query interfaces post-processing.

Support online queries for detailed transaction records spanning nearly 10 years.

Support online queries for detailed transaction records spanning nearly 10 years.

Integrate local and peripheral systems via API aggregation to enable unified data queries.

Deployed a unified stream-batch data computing service platform.

Established a unified query system with centralized storage/management for new core data and business-oriented query access.

Implemented Lambda architecture for backend stream-batch computing:

• Streaming ensures business-side timeliness

• Offline data validates/corrects real-time outputs

Abstracted underlying technical complexities to stabilize developer skill requirements, minimizing retraining needs despite infrastructure changes.

Enabled rapid data/service responses for time-sensitive scenarios like precision marketing and risk identification.

Enhanced mobile banking transaction inquiries by offering more detailed information, longer query periods, and more streamlined query steps.

Supported the bank’s next-generation core banking system, which adopts a distributed and modular deployment architecture. This resolves the performance challenges of cross-DUS (Distributed Unit System) queries when retrieving information based on customer ID across multiple institutional and teller-level databases.