银行是我国最主要的金融主体，对数据库及数据服务解决方案有着更高的性能与安全要求。随着金融数据应用服务的 快速发展，银行数据库所涉及的数据类型、业务场景更加多样化，用户很难在种类繁多的数据库产品和数据服务解决方案中 做出最优选择。为此，结合金融行业的数据应用发展需求，本文通过采用文献调研和理论分析等方法，全面分析了银行数据 库的应用现状，特别是近几年数据库国产化替代的情况与面临的挑战，系统调研了国内外主要的数据库测试基准，展望了构 建面向金融场景的下一代数据库测试基准的必要性和重要性。研究发现，由于金融场景中业务逻辑更复杂、数据模式更多 样、安全性要求更高等多方面原因，现有数据库测试基准在应对金融场景下的数据库测试时存在多处不足，面临着诸多挑 战，基于此，本文从工作负载、数据模式、度量指标以及技术架构等方面出发，对面向金融场景的下一代数据库测试基准的 构建提出针对性建议和要求。

As the major financial entity in China, banks have high performance and security requirements for databases and data service solutions. With the progression of data application services in banking, the data types and business scenarios become more diverse, and it is difficult for users to make optimal choices among a wide diversity of database products and data service solutions. In combination with the data application demands of the financial industry, this study comprehensively analyzes the current status of applications of databases in banking, particularly the status and challenges of database localization in recent years, by using literature research and theoretical analysis. In addition, we systematically investigate the database benchmarks of China and other countries, and further prospect the necessity and importance of constructing next-generation database benchmarks for financial scenarios. We find that current database benchmarks have many deficiencies and face various challenges in dealing with the database testing in financial scenarios owing to the complex business logic, diverse data patterns, and high security requirements. Therefore, to build a nextgeneration database benchmark that can meet the requirements of financial scenarios, we propose several suggestions to address these challenges, which involve the aspects of workloads, data schemes, metrics, and technical architecture.