Bank of Chongqing Independently Developed Analytical Database Procurement Project

In the Bank of Chongqing independently developed analytical database procurement project, the customer required replacing the existing Huawei GaussDB and demanded ecosystem compatibility with Kunpeng and Taishan servers, along with efficient support for t

Bank of Chongqing's Procurement of China-Developed Analytical Database

Project Background

 

In the procurement of a China-developed analytical database, Bank of Chongqing required the replacement of the existing Huawei GaussDB and ecosystem compatibility with Huawei Kunpeng and TaiShan servers, efficiently supporting traditional relational and structured data. Based on China-developed software and hardware ecosystems, it provides data analytics support for the bank’s accounting and credit systems.

 

 

Solution

The GBase 8a MPP analytical database is utilized to build a big data platform. The GBase 8a MPP high-speed data loading tool enables rapid data ingestion, synchronizing data from business systems such as bank accounting and credit to the data center in near-real time, effectively supporting analytical applications for historical data. Through GBase 8a MPP’s columnar storage, smart indexing, and high compression technologies, disk I/O access is significantly reduced, delivering a substantial performance improvement in query and statistical analysis over the original system. It supports ad-hoc queries and multidimensional analysis, powering complex BI application analysis and visualization.

Results

 

Cost Reduction: GBase 8a MPP Cluster runs on cost-effective China-developed chips and servers, effectively saving hardware investment and reducing scaling costs to approximately 1/10 of the original level.

 

Elastic Scaling: The horizontal scaling model of GBase 8a MPP Cluster nodes enables dynamic expansion without service interruption, ensuring business continuity.

 

High Availability: GBase 8a MPP Cluster enhances overall system synergy. Its multi-replica data high-availability strategy ensures that the failure of any node does not disrupt continuous service availability.